In the first of them (Table 1) we can assume the comments from a visual point of view of the qualitative comparison from Figures 2 and 3. We could consider OMED as the best suitable method because it is the best in five of the twelve analyzed sequences, while **Pearson** and OMDE are better in three videos each one. But, because of the fact that OMED is the worst in quality terms in several sequences (see the performance for the MR, IP3 and V2 scenes) we have incorporated a ranking index which scores each method in ascending order of its performance. Thus, the winner method for a sequence will obtain one point, the second two points, the third three points and the forth four points. The last row of the Table 1 represents the sum of these scores for all the sequences. From these results, we can conclude that **Pearson** is the best method on average because, although it is not always the best, it is the second best method in most of the sequences (see the ranking of the methods in Table 3). Therefore, this approach could be viewed as the most stable method regardless of the type of sequence. It is interesting to observe that, except one case and with low margin (sequence V2 ), the **Pearson** **correlation** filtering always improves the result produced by the Basic segmentation algorithm.

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Abstract—Epilepsy is a disease caused by an excessive discharge of a group of neurons in the cerebral cortex. Extracting this information using EEG signals is an ongoing challenge in biomedical signal processing. In this paper, a new method is proposed for onset seizure detection in epileptic EEG signals based on parameters from the t-location-scale distribution coupled with the variance and the **Pearson** **correlation** coefficient. The 1-nearest neighbor classifier achieved a 91% sensitivity (True positive rate) and 95% specificity (True Negative Rate) with a delay of 4.5 seconds (on average) in the 45 signals analyzed, which suggests that the proposed methodology is potentially useful for seizure onset detection in epileptic EEG signals.

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SZnC in both samples was verified, the data were expressed as the mean ± SD or median (min-max) where appropriate. The **Pearson** **correlation** coefficient, the simple linear regres- sion analysis, the B&A method −the difference between meth- ods and the difference between the methods expressed as a percentage [(FAAS - Colorimetric method)/percentage of the mean]−, and CCC were computed to study relations between methods. Finally, the comparison of hypozincemia between methods was based upon the percentages of cases, using the following cut-off points: SZNC <70 µg/dl in children under 10 years of both sexes and in women aged 10 or older years, and <74 µg/dl in men aged 10 years or more 2 . Different cut-

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Table 1 shows the models obtained for the three experimental sites; it shows that the values of the determination coefficient varied from 0.766 to 0.899 and are similar to those recorded by Moreno et al. (2018) with 0.965 to 0.969, as well as those of Del Valle (2003) with 0.966, as well as those of Ibarra et al. (2011) with 0.946 and Martínez et al. (2007) with 0.698 to 0.821. For this reason, the Negative Simple Exponential Model (1) is the best fit according to the determination coefficient and the **Pearson** **correlation** coefficient for the three types of forests. The **correlation** coefficient was distributed in a range between 0.875 and 0.948 for the model (1). It can be seen that the Negative Simple Exponential Model is the best fit based on the highest value of the **Pearson** determination coefficient and **correlation** coefficient, as well as the lowest RECM for the three types of forest.

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Abstract: Phosphorus (P) is essential to all known life forms because it is a key element in many physiological and biochemical processes. Soil properties due to soil formation processes and land use have an impact on the availability of phosphorus in soil and on the change in geochemical fractions. The phosphorus fractions are important for assessing their soil status and understanding the soil chemistry that affects soil fertility. Taken 43 soil samples, were selected from agricultural fields of Isparta - Southeast of Turkey, to determine the availability of phosphorus and change in fractions. Relations of phosphorus fractions with soil properties were revealed by analysis of variance, **Pearson** **correlation** analysis Descriptive physicochemical analyzes and sequential phosphorus fractionation were performed in the soil. These fractions are; sodium bicarbonate (NaHCO 3 -P) , sodium hydroxide (NaOH-P), citrate bicarbonate dithionite (CBD-P), hydrochloric acid (Ca-P), and residual (Res-P) phosphorus. The results showed that the fractionations (Ca-P, 597.05 mg kg -1 ) (Res-P, 259.54 mg kg -1 ) were high for respectively. It was

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The first and the second generic information loss measures which we analyse are average distance and diameter. Both measures are related to paths and cannot be calcu- lated for graphs with two or more connected components. Thus, both measures cannot be computed on few perturbed graphs because isolated nodes have appeared during perturbation process. The **Pearson** **correlation** index for average distance and the pre- cision for all clustering methods is 0.732. As we can see in Table 5, average distance achieves strong **correlation** values with all clustering methods, except with MCL, where the achieved value is quite lower than others and indicates a moderate **correlation** be- tween average distance and the precision values of MCL clustering. As we can see, p- values are 0 for all experiments, demonstrating that results are statistically significant. On the contrary, diameter does not present **correlation** since its p-values are greater than 0.05 on three experiments, and no statistical significance can be assigned to its **correlation** value. In addition, the **correlation** value is 0.128, which is very low.

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the Center for Research Support of Complutense University of Madrid, Spain. Changes over time in BW, BCS, BMI, length, and metabolic indices of sheep and lambs were assessed for significance using ANOVA for repeated measures in a general linearized model with Greenhouse-Geisser correction. Differences between groups at different time points were assessed for significance using non-parametric analysis, the Kruskal-Wallis test or the Mann-Whitney test, after confirming the skewed (non-normal) distribution of the data. Inter-group differences in body circumference, average daily gain and metabolic indices in lambs were also assessed for significance using the independent t test. **Pearson** **correlation** coefficients were calculated to assess the strength of potential relationships between sheep variables, or of relationships of lamb birth weight with maternal

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Fig. 2 shows the MAE results obtained on MovieLens 1M using various similarity measures and two aggregations approaches commonly used in CF (Eqs. (16) and (17)). The calculations have been made in the range K=2 to K=1500, by averaging their results; as we can see, the lowest error values are obtained using **Pearson** **Correlation** (PC), particularly when Deviation From Mean (DFM) is used as the aggregation approach. These results lead us to use PC-DFM as the reference combination which acts as a way of testing future metrics proposed by the scientific community, although it still needs to be tested with standardization methods, analysis of its coverage, quality of recommendations, etc.

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To conclude, in this work we propose an extension of the Grassberger-Procaccia method to estimate the **correlation** dimension of a complex network from the analysis of the trajectories of random walkers on top of them. Although the original method was initially designed as a tool to retrieve the attractor dimension of low-dimensional chaotic dynamics, the presence of temporal correlations in stochastic dynamics (here induced by the geometry of the network) also produces similar behaviors under this celebrated framework [27,36]. Thus, in this work we delib- erately exploit this property when using random walks as the trajectories under study. This probes the possibility of making use of concepts and tools from the ergodic theory of dynamical systems in the realm of complex networks.

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Abstract The present work applies similarity theory to the plasma emanating from transferred arc, gas-vortex stabilized plasma cutting torches, to analyze the existing **correlation** between the arc temperature and the physical parameters of such torches. It has been found that the enthalpy number significantly influence the temperature of the electric arc. The obtained **correlation** shows an average deviation of 3 % from the temperature data points. Such **correlation** can be used, for instance, to predict changes in the peak value of the arc temperature at the nozzle exit of a geometrically similar cutting torch due to changes in its operation parameters.

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The **Pearson** **correlation** coeffi cient (r) between the grip strength and hand-forearm anthropometry was found to determine either existing or not a linear relation among them. Collecting data of the variables was obtained from ten young adults in both, right and left hand-forearm, it was taken into account some qualitative variables: to be right-handed, the gender with fi ve (5) men and fi ve (5) women, and it was established as a condition that the individual was healthy and did not have a previous career as an athlete. A direct linear relationship with hand anthropometry and the grip strength is concluded, even though as expected, there was a strong difference between the force exerted by a male and a female individual, being the fi rst stronger. Respect to the forearm, an inverse relation was found between the maximum circumference of the forearm and the grip strength. Finally, the strongest relationships found were in the width and length of the palm, as well as in the circumference of the wrist. Results were validated comparing the results of this research against the results of specialized literature. Some considerations may be considered for future research. Grip strength can promote the risk of accidents and ergonomists should consider this factor appropriately for their design.

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The purpose of the study is to determine the relationship between the learning styles and the academic performance of the 4th grade students of the Educational Institution Nº 36223 of Huanca Huanca, in Huancavelica in the year 2017. The Honey Alonso questionnaire was administered. Learning Styles (CHAEA) to a sample of 38 students of the 4th grade of primary school Educational Institution Nº 36223 of Huanca Huanca. A positive and significant relationship was found between the learning styles in general and the academic performance of the 4th grade students of the Educational Institution Nº 36223 of Huanca Huanca, in Huancavelica in the year 2017. This is reflected in table 12 which indicates that there is a **Pearson** **correlation** coefficient of 0.699 that represents a very significant relationship between learning styles in general and academic performance. Likewise, it should be mentioned that in terms of the predominant learning style in the students, it was found that the active learning style was the predominant one (mean = 11.26). In this regard, on learning styles in general (active, theoretical, reflective and pragmatic) we can say that a greater mastery of a learning style corresponds to a higher academic performance, and in its absence to a lesser mastery of a style of learning corresponds to a lower level of academic performance.

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Here -1 indicates a perfect inverse linear relationship, i.e. “y” increases uniformly as “x” decreases, and 1 indicates a perfect direct linear relationship, i.e. “x” and “y” move uniformly together. A value of 0 indicates no relationship. Note that **correlation** can determine that a relationship exists between variables but says nothing about the cause or directional effect. For example, a known **correlation** exists between muggings and ice cream sales. However, one does not cause the other. Rather, a third variable, the warm weather which puts more people on the street both to mug and buy ice cream is a more direct cause of the **correlation**.

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As far as socio-economic status is concerned, the eight traits proposed for assessing enterprising personality present a small percentage of common variance with this variable (1.6%). It would not appear, therefore, that socio-economic status is a determining factor in the development of the enterprising personality. These results are in line with those obtained by Stewart, May, and Kalia (2008), who found no relationships between socio-economic variables and entrepreneurial behaviour. Nevertheless, and as various authors have suggested, growing up in an enterprising family context can reinforce personal and social development oriented towards entrepreneurial behaviour (Altinay, Madanoglu, Daniele, & Lashley, 2012; Schroder, Schmitt-Rodermund, & Arnaud, 2011). Nor did we fi nd very high correlations between the eight dimensions of enterprising personality and academic performance: the multiple **correlation** between these eight dimensions and Mathematics performance was .362, whilst it was .513 for the case of Spanish Language and Literature. The personality dimensions most closely related to academic performance were achievement motivation (r = .23 with Mathematics and r = .24 with Spanish Language and Literature) and autonomy (r = .32 with Mathematics and r = .37 with Spanish Language and Literature). These data point in the direction that the enterprising personality cannot be clearly linked to academic performance, since even though the correlations are positive, they are not high. This aspect is of considerable applied importance, and knowledge about it can help in the design of programmes for education and training in entrepreneurial skills for young people. Another relevant question is whether or not teachers are able to identify those students who show entrepreneurial inclinations. The data seem to suggest that teachers are not very effective when it comes to detecting entrepreneurial students, since the multiple **correlation** between the eight enterprising personality dimensions and teachers’ ratings yielded a value of .385, meaning that teachers only predicted around 13% of enterprising personality in their students. This fi nding highlights the need for objective measurement instruments to assess enterprising personality, such as the BEPE described in the present study, which could be of help to teachers and counsellors aiming to boost and train their students’ entrepreneurial capacity. Finally, students’ self-ratings also showed only a modest **correlation** with the eight personality dimensions assessed, as the associated percentage of variance between the BEPE and the overall self-ratings was just 19%.

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tenga distribución límite Ji cuadrado que es continua. Frank Yates (1934) sugiere una corrección para continuidad la cual ajusta la dócima Ji cuadrado de **Pearson** sustrayendo 0.5 desde la diferencia en módulo existente entre frecuencia observada y frecuencia esperada para tablas de contingencias 22. Esta corrección es conveniente para cuando se tienen células con frecuencias esperadas menor que 5. Su expresión es:

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Abstract: The semi-arid Caatinga is the fourth largest biome of Brazil, which biota still remains one of the most poorly known, especially with regard to invertebrate groups. In this study, a ground-foraging ant assemblage was surveyed during one year and the effect of rainfall on pitfall trapping was assessed. The study was performed in an area located in the municipality of Pentecoste (3º48’ S - 39º20’ W), in the State of Ceará. A 200m transect with 20 equidistant sampling points was established. Transect sampling was performed once a month during 12 months, over the period August 2008-August 2009. At each sampling point, a pitfall trap partially filled with a mixture of ethanol and monoethylene glycol was placed at the beginning of each month and remained in the field for seven days. 39 species belonging to six subfamilies and 19 genera, plus two unidentified species, were collected, with Pheidole (10 spp.) and Camponotus (8 spp.) being the taxa with the most species. 23 species were frequent, being found in more than 50% of the 12 transect samplings. Five species had an intermediate frequency (25 to 50%), while 13 were relatively infrequent (less than 25%). Most of the species (22) showed low occurrence, being found in less than 10% of the 240 samples (20 samples each month, during 12 months). Only five species were collected in more than 50% of the samples, those species being also responsible for most of the total abundance (number of captured individuals of all species) observed each month. The species- accumulation curves (observed and estimated) indicated that sampling sufficiency was attained, and that about 92% of the estimated ground-foraging ant fauna had been collected. 40 and 29 species were collected in the dry and rainy season, respectively, with monthly species richness ranging from 13 to 28. The total ant abundance showed a drastic decrease during the rainy season, and a negative linear **correlation** was found between rainfall and total ant abundance (R 2 =0.68). A similar negative linear **correlation** was found for species occurrences

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To obtain a quantitative measure of the degree of association between the two variables, Select Correlate Bivariate from the Analyze pull-down menu. In the dialogue box, move the two variables % immunization and rate mortality into the Variables frame. Make sure that **Pearson** is selected in the **Correlation** Coefficients frame and that Two-tailed is selected in the Test of Significance frame. Click OK. Take a look at the output table: What is the **correlation** between the two variables? Is it significant?

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Se observa que para un mismo valor en inteligencia existen diferentes posibles valores en rendimiento. Se trata de una correlación positiva pero no perfecta. Este conjunto de puntos, denominado diagrama de dispersión o nube de puntos tiene interés como primera toma de contacto para conocer la naturaleza de la relación entre dos variables. Si tal nube es alargada -apunta a una recta- y ascendente como es el caso que nos ocupa, es susceptible de aplicarse el coeficiente lineal de **Pearson**. El grosor de la nube da una cierta idea de la magnitud de la correlación; cuanto más estrecha menor será el margen de variación en Y para los valores de X, y por tanto, más acertado los pronósticos, lo que implica una mayor correlación.

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B.- La teoría de los actos de habla de Austin. Una vez descritas las diferentes unidades objeto de estudio y aplicando el programa de extracción automática de términos CLG tagger, es decir, Corpus Linguistics Group de la Universidad de Birmingham, el proceso de recuperación de la información se establece en tres etapas: una primera etapa manual en la que se desarrollan los modelos de marcación que se utilizarán como entrada al programa para obtener las concordancias con esos modelos; una segunda etapa consistente en la obtención de los resultados de la aplicación; y una tercera etapa de refinamiento de los resultados de ese análisis, debido a que no todas las concordancias obtenidas responden a términos en ese corpus concreto, en base a dos criterios restrictivos adicionales: el criterio denominado generic reference, según el cual sólo aquellos candidatos que **Pearson** llama unflagged (en oposición a flagged, es decir, precedidos por un número de determinantes excepto el artículo indefinido), esto es, precedidos por el artículo indefinido o por ningún artículo, son términos; y un segundo criterio denominado linguistic signals, es decir, que todos los candidatos a término deberían serlo si ocurren al menos una vez con alguna de las señales lingüísticas propuestas (entre ellas, called, known as, e.g., the term o “(...)”).

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As the results of the multiple regression analysis for high and low students indicates, despite the significant **correlation**, neither depth nor breadth of vocabulary knowledge were significant predictors of listening comprehension in low proficient students. In high proficient students, on the other hand, the prediction afforded by breadth was significant and, quite interestingly, it was found that depth of vocabulary knowledge was not a significant predictor of listening comprehension in the high group. In explanation, it is necessary to refer to manifold notes of and positions taken by vocabulary researchers on the relationship between breadth and depth dimensions of vocabulary knowledge. Vemeer (2001, p. 230), for instance, argues that ‘deeper knowledge of words is the consequence of knowing more words, or that, conversely, the more words someone knows, the finer the network and the deeper the word knowledge’. Similarly, Milton (2009: 169) emphasizes the close affinity between depth and breadth of vocabulary knowledge and states that ‘… qualities of depth really seem to appear only after a sizeable vocabulary breadth has been attained’. Milton (2013) even goes further and claims that breadth and depth of vocabulary knowledge are essential components of the same dimension. Drawing on the above theoretical stances, it can be assumed that higher proficiency students have developed a larger vocabulary repertoire and, consequently, deepened their word knowledge. In this group of students, the demarcating boundaries between depth and breadth have vanished with growth in language proficiency level. Thus, as long as there is a high **correlation** between depth and breadth, considering these two variables separately in high proficiency students is meaningless and contribution of breadth equals to the

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