Journal articles on the topic 'Correlation-extreme systems'
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Coletti, G., L. C. van der Gaag, D. Petturiti, and B. Vantaggi. "Detecting correlation between extreme probability events." International Journal of General Systems 49, no. 1 (November 21, 2019): 64–87. http://dx.doi.org/10.1080/03081079.2019.1692005.
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Calderón-Vega, Felícitas, Adrián-David García-Soto, and César Mösso. "Correlation of Concurrent Extreme Metocean Hazards Considering Seasonality." Applied Sciences 10, no. 14 (July 13, 2020): 4794. http://dx.doi.org/10.3390/app10144794.
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Simultaneous occurrence of metocean variables can present a multihazard to maritime systems. However, simplified design approaches to assess simultaneous significant wave heights and wind velocities are lacking, especially if seasonality is considered. This is addressed in this study by using extreme significant wave heights and companion wind velocities recorded in the Gulf of Mexico. Time-dependent, generalized extreme value (GEV) models and classical regression are the basis to propose a simplified approach to estimate correlated extreme significant wave heights and wind velocities associated with given return periods, accounting for seasonality and including measures of uncertainty. It is found that the proposed approach is a new but simple method to adequately characterize the concurrent extreme metocean variables and their uncertainty. It is concluded that the method is an effective probabilistic design tool to determine simultaneous extreme significant wave heights and companion wind velocities for desired return periods and seasonality.
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Kharchenko, Volodymyr, and Maryna Mukhina. "CORRELATION-EXTREME VISUAL NAVIGATION OF UNMANNED AIRCRAFT SYSTEMS BASED ON SPEED-UP ROBUST FEATURES." Aviation 18, no. 2 (July 2, 2014): 80–85. http://dx.doi.org/10.3846/16487788.2014.926645.
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The peculiarities of correlation-extreme visual navigation are considered. Descriptors with 64 elements of feature points of surface images are selected on the basis of the speed-up robust feature method. An analysis of possible criteria correlation functions is carried out to find the best match between the template descriptors and current images. The use of normalized correlation function is proposed based on the matrix multiplication properties of descriptors. It allows minimizing the number of false matches in comparison with the Euclidean distance in the descriptor space. The proposed matching strategy sufficiently decreases the computation time.
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Tantsiura, Alexander. "Evaluation of the Potential Accuracy of Correlation Extreme Navigation Systems of Low-Altitude Mobile Robots." International Journal of Advanced Trends in Computer Science and Engineering 8, no. 5 (October 15, 2019): 2161–66. http://dx.doi.org/10.30534/ijatcse/2019/47852019.
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Kozhushko, Yaroslav. "Determination of Accuracy of Low-Altitude Navigation of Dynamic Objects Equipped with Correlation-Extreme Systems." International Journal of Advanced Trends in Computer Science and Engineering 9, no. 3 (June 25, 2020): 2981–86. http://dx.doi.org/10.30534/ijatcse/2020/75932020.
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Hamada, Atsushi, Yuki Murayama, and Yukari N. Takayabu. "Regional Characteristics of Extreme Rainfall Extracted from TRMM PR Measurements." Journal of Climate 27, no. 21 (October 24, 2014): 8151–69. http://dx.doi.org/10.1175/jcli-d-14-00107.1.
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Abstract Characteristics and global distribution of regional extreme rainfall are presented using 12 yr of the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) measurements. By considering each rainfall event as a set of contiguous PR rainy pixels, characteristic values for each event are obtained. Regional extreme rainfall events are defined as those in which maximum near-surface rainfall rates are higher than the corresponding 99.9th percentile on a 2.5° × 2.5° horizontal-resolution grid. The geographical distribution of extreme rainfall rates shows clear regional differences. The size and volumetric rainfall of extreme events also show clear regional differences. Extreme rainfall rates show good correlations with the corresponding rain-top heights and event sizes over oceans but marginal or no correlation over land. The time of maximum occurrence of extreme rainfall events tends to be during 0000–1200 LT over oceans, whereas it has a distinct afternoon peak over land. There are also clear seasonal differences in which the occurrence over land is largely coincident with insolation. Regional extreme rainfall is classified by extreme rainfall rate (intensity) and the corresponding event size (extensity). Regions of “intense and extensive” extreme rainfall are found mainly over oceans near coastal areas and are likely associated with tropical cyclones and convective systems associated with the establishment of monsoons. Regions of “intense but less extensive” extreme rainfall are distributed widely over land and maritime continents, probably related to afternoon showers and mesoscale convective systems. Regions of “extensive but less intense” extreme rainfall are found almost exclusively over oceans, likely associated with well-organized mesoscale convective systems and extratropical cyclones.
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Salgueiro, João Hipólito Paiva de Britto, Suzana Maria Gico Lima Montenegro, Eber José de Andrade Pinto, Bernardo Barbosa da Silva, Werônica Meira de Souza, and Leidjane Maria Maciel de Oliveira. "Influence of oceanic-atmospheric interactions on extreme events of daily rainfall in the Sub-basin 39 located in Northeastern Brazil." RBRH 21, no. 4 (October 24, 2016): 685–93. http://dx.doi.org/10.1590/2318-0331.011616023.
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ABSTRACT Changes in extreme precipitation have been observed in regions where frequent rainfalls occur over short periods of time followed by prolonged droughts, creating, as a result, new watershed scenarios. Recent studies have attributed such occurrences to possible climate changes. This paper analyzes the correlation between extreme events recorded in the Sub-basin 39, located in Northeastern Brazil, and the anomalies caused by sea surface temperature - SST and the atmospheric systems operating in the region. Pearson correlation coefficients have been used combined with the variables analyzed. For such, trends in precipitation have been obtained by using the method of least squares together with linear regression and the Student's t test. The results obtained have demonstrated that due to the geographical position of the region investigated, both maximum extreme events (areas with positive trends) and minimum extreme events (areas with negative trends) are more dependent on the Dipole Atlantic than on the effects of El Niño Southern Oscillation - ENOS.
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Liashko, Olha. "The Criterion and Evaluation of Effectiveness of Image Comparison in Correlation-Extreme Navigation Systems of Mobile Robots." International Journal of Emerging Trends in Engineering Research 8, no. 6 (June 25, 2020): 2841–47. http://dx.doi.org/10.30534/ijeter/2020/97862020.
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Dawley, Shawn, Yong Zhang, Xiaoting Liu, Peng Jiang, Geoffrey Tick, HongGuang Sun, Chunmiao Zheng, and Li Chen. "Statistical Analysis of Extreme Events in Precipitation, Stream Discharge, and Groundwater Head Fluctuation: Distribution, Memory, and Correlation." Water 11, no. 4 (April 5, 2019): 707. http://dx.doi.org/10.3390/w11040707.
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Hydrological extremes in the water cycle can significantly affect surface water engineering design, and represents the high-impact response of surface water and groundwater systems to climate change. Statistical analysis of these extreme events provides a convenient way to interpret the nature of, and interaction between, components of the water cycle. This study applies three probability density functions (PDFs), Gumbel, stable, and stretched Gaussian distributions, to capture the distribution of extremes and the full-time series of storm properties (storm duration, intensity, total precipitation, and inter-storm period), stream discharge, lake stage, and groundwater head values observed in the Lake Tuscaloosa watershed, Alabama, USA. To quantify the potentially non-stationary statistics of hydrological extremes, the time-scale local Hurst exponent (TSLHE) was also calculated for the time series data recording both the surface and subsurface hydrological processes. First, results showed that storm duration was most closely related to groundwater recharge compared to the other storm properties, while intensity also had a close relationship with recharge. These relationships were likely due to the effects of oversaturation and overland flow in extreme total precipitation storms. Second, the surface water and groundwater series were persistent according to the TSLHE values, because they were relatively slow evolving systems, while storm properties were anti-persistent since they were rapidly evolving in time. Third, the stretched Gaussian distribution was the most effective PDF to capture the distribution of surface and subsurface hydrological extremes, since this distribution can capture the broad transition from a Gaussian distribution to a power-law one.
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Vieira, Fabrício, Maurício Ribeiro, Antonio Francisco, and Giane Gonçalves Lenzi. "Influence of Extreme Events in Electric Energy Consumption and Gross Domestic Product." Sustainability 11, no. 3 (January 28, 2019): 672. http://dx.doi.org/10.3390/su11030672.
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The objective of this paper was to identify how extreme events can indicate periods of economic instability in variables from the economic and environmental context (per capita Gross Domestic Product (GDP), per capita electric energy consumption, and per capita carbon dioxide (CO2) emission). The research is limited to the population of the country (Brazil) and five cities of Paraná (Curitiba, Londrina, Maringá, Ponta Grossa, and Cascavel). Therefore, the major research interest was focused on finding information related to extreme events and other techniques that are used for interpretation of complex systems currently. The development was based on data collection. The results indicated that extreme events have influence in periods of economic instability. They also evidenced that there is greater correlation in GDP data/electric energy consumption than in GDP data/CO2 emissions or electric energy consumption/CO2 emissions.
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Diro, G. T., and H. Lin. "Subseasonal Forecast Skill of Snow Water Equivalent and Its Link with Temperature in Selected SubX Models." Weather and Forecasting 35, no. 1 (February 2020): 273–84. http://dx.doi.org/10.1175/waf-d-19-0074.1.
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AbstractAccurate and skillful subseasonal forecasts have tremendous potential for sectors that are sensitive to hazardous weather and climate events. Analysis of prediction skill for snow water equivalent (SWE) and near-surface air temperature (T2m) is carried out for three (GEPS, GEFS, and FIM) global models from the subseasonal experiment (SubX) project for the 2000–14 period. The prediction skill of SWE is higher than the skill of T2m at week-3 and week-4 lead times in all models. The GEPS forecast tends to yield higher (lower) prediction skill of SWE (T2m) compared to the other two systems in terms of correlation skill score. The snow–temperature relationship in reanalysis is characterized by a strong negative correlation over most of the midlatitude regions and a weak positive correlation over high-latitude Arctic regions. All forecast systems reproduced well these observed features; however, the snow–temperature relationship is slightly weaker in the GEPS model. Despite the apparent lack of skill in temperature forecasts at week 4, all three models are able to predict the sign of temperature anomalies associated with extreme SWE conditions albeit with reduced intensity. The strength of the predicted temperature anomaly associated with extreme snow conditions is slightly weaker in the GEPS forecast compared to reanalysis and the other two models, despite having better skill in predicting SWE. These apparent disparities suggest that weak snow–temperature coupling strength in the model is one of the contributing factors for the lower temperature skill.
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Shashidhar, Ravindranath, Sanjukta A. Kumar, Hari S. Misra, and Jayant R. Bandekar. "Evaluation of the role of enzymatic and nonenzymatic antioxidant systems in the radiation resistance of Deinococcus." Canadian Journal of Microbiology 56, no. 3 (March 2010): 195–201. http://dx.doi.org/10.1139/w09-118.
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Antioxidant enzymes and antioxidant metabolites appear to have different roles in the oxidative stress resistance responses of radiation-resistant bacteria belonging to the Deinococcus – Thermus group. Twelve distinct strains belonging to 7 Deinococcus species were characterized for their responses to hydrogen peroxide, ciprofloxacin, and ionizing radiation. The levels of catalase and peroxidase activities in these strains showed a positive correlation with resistance to hydrogen peroxide and ciprofloxacin. However, the levels of these enzymes and carotenoids did not appear to contribute significantly to radiation resistance. Our findings support the idea that enzymatic defense systems are not sufficient to account for the extreme radiation resistance of Deinococcus species. Consistent with previously published reports, the Deinococcus strains had high intracellular manganese/iron ratios. No significant correlation was found between intracellular manganese/iron ratios and radiation resistance within different Deinococcus species, suggesting that other components are involved in conferring radiation resistance.
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Tsonis, A. A., and K. P. Georgakakos. "Observing extreme events in incomplete state spaces with application to rainfall estimation from satellite images." Nonlinear Processes in Geophysics 12, no. 2 (February 2, 2005): 195–200. http://dx.doi.org/10.5194/npg-12-195-2005.
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Abstract. Reconstructing the dynamics of nonlinear systems from observations requires the complete knowledge of its state space. In most cases, this is either impossible or at best very difficult. Here, by using a toy model, we investigate the possibility of deriving useful insights about the variability of the system from only a part of the complete state vector. We show that while some of the details of the variability might be lost, other details, especially extreme events, are successfully recovered. We then apply these ideas to the problem of rainfall estimation from satellite imagery. We show that, while reducing the number of observables reduces the correlation between actual and inferred precipitation amounts, good estimates for extreme events are still recoverable.
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Liu, Yue Fei, and Da Gang Lu. "Time-Dependent Reliability Prediction Analysis of Bridge Members Considering Dependence of Failure Modes and Proof Modes." Key Engineering Materials 648 (June 2015): 25–34. http://dx.doi.org/10.4028/www.scientific.net/kem.648.25.
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Structural health monitoring systems used in bridges contain sensors providing a large amount of monitored data, such as stress, deflection and et.al. In this paper, firstly, based on monitored everyday extreme stress data, time-variant proof load effects of structural members were defined, and based on the time-dependent proof load effects, the time-dependent performance functions of structural member’s proof modes were built; and then based on the monitored data, the Bayesian dynamic models (BDMs) of extreme stresses were built, and based on the predicted extreme stress with BDMs, the time-variant performance functions of structural member’s failure modes were given; and then based on the time-dependent performance functions of failure modes and proof modes and correlation coefficients between them, with the conditional probability method, the time-dependent reliability indices of structural members were updated and predicted; finally an actual engineering was provided to illustrate the application of the proposed models and methods.
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Gong, Song Jie. "An Enhanced Similarity Measure Used in Personalized Recommendation Algorithms." Advanced Materials Research 159 (December 2010): 671–75. http://dx.doi.org/10.4028/www.scientific.net/amr.159.671.
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Personalized recommendation systems combine the data mining technology with users browse profile and provide recommendation set to user forecasted by their interests. Collaborative filtering algorithm is one of the most successful methods for building personalized recommendation system, and is extensively used in many fields to date. With the development of E-commerce, the magnitudes of users and items grow rapidly, resulting in the extreme sparsity of user rating data. Traditional similarity measure methods work poor in this situation, make the quality of recommendation system decreased dramatically. To alleviate the problem, an enhanced Pearson correlation similarity measure method is introduced in the personalized collaborative filtering recommendation algorithm. The approach considers the common correlation rating of users. The recommendation using the enhanced similarity measure can improve the neighbors influence in the course of recommendation and enhance the accuracy and the quality of recommendation systems effectively.
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Li, Shuang, Feili Wei, Zheng Wang, Jiashu Shen, Ze Liang, Huan Wang, and Shuangcheng Li. "Spatial Heterogeneity and Complexity of the Impact of Extreme Climate on Vegetation in China." Sustainability 13, no. 10 (May 20, 2021): 5748. http://dx.doi.org/10.3390/su13105748.
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The impact of extreme climate on natural ecosystems and socioeconomic systems is more serious than that of the climate’s mean state. Based on the data of 1698 meteorological stations in China from 2001 to 2018, this study calculated the 27 extreme climate indices of the Expert Team on Climate Change Detection and Indices (ETCCDI). Through correlation analysis and collinearity diagnostics, we selected two representative extreme temperature indices and three extreme precipitation indices. The spatial scale of the impact of extreme climate on Normalized Difference Vegetation Index (NDVI) in China during the growing season from 2001 to 2018 was quantitatively analyzed, and the complexity of the dominant factors in different regions was discussed via clustering analysis. The research results show that extreme climate indices have a scale effect on vegetation. There are spatial heterogeneities in the impacts of different extreme climate indices on vegetation, and these impacts varied between the local, regional and national scales. The relationship between the maximum length of a dry spell (CDD) and NDVI was the most spatially nonstationary, and mostly occurred on the local scale, while the effect of annual total precipitation when the daily precipitation amount was more than the 95th percentile (R95pTOT) showed the greatest spatial stability, and mainly manifested at the national scale. Under the current extreme climate conditions, extreme precipitation promotes vegetation growth, while the influence of extreme temperature is more complicated. As regards intensity and range, the impact of extreme climate on NDVI in China over the past 18 years can be categorized into five types: the humidity-promoting type, the cold-promoting and drought-inhibiting compound type, the drought-inhibiting type, the heat-promoting and drought-inhibiting compound type, and the heat-promoting and humidity-promoting compound type. Drought is the greatest threat to vegetation associated with extreme climate in China.
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Yeromina, Nataliia, Serhii Petrov, Maksym Volk, Olena Daki, Volodymyr Cherednyk, Iryna Zinchenko, Ihor Chernykh, Oleksiy Alekseienko, Serhii Mykus, and Volodymyr Furdyk. "Synthesis of an optimal digital filter of a compensation radiometer for radiometric correlation-extreme navigation systems of unmanned aerial vehicles." Eastern-European Journal of Enterprise Technologies 2, no. 9 (110) (April 30, 2021): 79–86. http://dx.doi.org/10.15587/1729-4061.2021.230176.
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The expediency of using a compensation radiometer (CR) with periodic absolute calibration as a sensor for preprocessing the information of correlation-extreme navigation systems (CENS) of unmanned aerial vehicles (UAV) was shown. This is determined by the possibility of obtaining and using the estimates of gain fluctuations obtained in previous frames which will provide an increase in the radiometer sensitivity. In addition, due to the accumulation of information, an increase in accuracy of measurement of the elements of the current image formed by the CENS will be provided. The algorithm of processing the obtained calibration estimates during linear processing corresponds to a certain digital filter (DF). By defining a set of the DF weight coefficients, it is possible to improve the CR fluctuation sensitivity by reducing the gain fluctuations. Up to 1.8-time gain in sensitivity can be reached for typical frequency and time parameters of the compensation radiometer of UAV CENS. The problem of synthesis of a digital filter was set. A solution to the problem of synthesizing an optimal digital filter was proposed. Its use in a CR will improve the fluctuation sensitivity. In its turn, this will make it possible to improve the quality of a current image generated by the system when siting by means of sighting surfaces with low-contrast objects taking into account fluctuations in radio-brightness temperature. It was found that the gain in sensitivity when using the optimal digital filter increases with an increase in the operating period of the radiometer and an increase in the digital filter order. Improvement of fluctuation sensitivity of the CENS data preprocessing system is important for UAV location in low-contrast areas
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Tang, Shu Min, Li Ma, Shi Yao Lu, Yu Meng Wang, Ka Wai Kam, Pancy O. S. Tam, Alvin L. Young, Chi Pui Pang, Jason C. S. Yam, and Li Jia Chen. "Association of the PAX6 gene with extreme myopia rather than lower grade myopias." British Journal of Ophthalmology 102, no. 4 (February 7, 2018): 570–74. http://dx.doi.org/10.1136/bjophthalmol-2017-311327.
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AimsTo investigate the association of the paired box gene 6 (PAX6) with different severities of myopia.MethodsA total of four haplotype-tagging single-nucleotide polymorphisms (SNPs; rs2071754, rs3026354, rs3026390 and rs628224) and two previously reported SNPs (rs644242 and rs662702) in the PAX6 gene were analysed in a Hong Kong Chinese cohort of 1288 myopia subjects (including 252 extreme myopia, 277 high myopia, 393 moderate myopia and 366 mild myopia) and 791 no myopia controls. Allelic association analyses were performed for individual SNPs in different subgroups of myopia and in combined myopia, followed by a meta-analysis of our current data with reported data on PAX6 in myopia.ResultsThe association of tagging SNPs rs2071754 and rs644242 with extreme myopia could not withstand multiple correction (rs2071754: OR=1.25, P value=0.031; rs644242: OR=1.33, P value=0.032). In the meta-analysis, rs644242 showed an enhanced, significant association with extreme myopia (OR=1.27, 95% CI 1.10 to 1.46, P value=0.001; I2=0%). In contrast, there was no significant association between the PAX6SNPs and high, moderate or mild myopia. No linear correlation was found between the PAX6SNPs and axial length.ConclusionThis study provides additional evidence suggesting that the PAX6 SNP rs644242 is associated with extreme myopia but not lower grade myopia. Thus, PAX6 may be implicated in the development or progression into severe myopia. Further longitudinal studies are warranted.
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Fitzpatrick, Rory G. J., Douglas J. Parker, John H. Marsham, David P. Rowell, Francoise M. Guichard, Chris M. Taylor, Kerry H. Cook, et al. "What Drives the Intensification of Mesoscale Convective Systems over the West African Sahel under Climate Change?" Journal of Climate 33, no. 8 (April 15, 2020): 3151–72. http://dx.doi.org/10.1175/jcli-d-19-0380.1.
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AbstractExtreme rainfall is expected to increase under climate change, carrying potential socioeconomic risks. However, the magnitude of increase is uncertain. Over recent decades, extreme storms over the West African Sahel have increased in frequency, with increased vertical wind shear shown to be a cause. Drier midlevels, stronger cold pools, and increased storm organization have also been observed. Global models do not capture the potential effects of lower- to midtropospheric wind shear or cold pools on storm organization since they parameterize convection. Here we use the first convection-permitting simulations of African climate change to understand how changes in thermodynamics and storm dynamics affect future extreme Sahelian rainfall. The model, which simulates warming associated with representative concentration pathway 8.5 (RCP8.5) until the end of the twenty-first century, projects a 28% increase of the extreme rain rate of MCSs. The Sahel moisture change on average follows Clausius–Clapeyron scaling, but has regional heterogeneity. Rain rates scale with the product of time-of-storm total column water (TCW) and in-storm vertical velocity. Additionally, prestorm wind shear and convective available potential energy both modulate in-storm vertical velocity. Although wind shear affects cloud-top temperatures within our model, it has no direct correlation with precipitation rates. In our model, projected future increase in TCW is the primary explanation for increased rain rates. Finally, although colder cold pools are modeled in the future climate, we see no significant change in near-surface winds, highlighting avenues for future research on convection-permitting modeling of storm dynamics.
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RONG, HAI-JUN, GUANG-BIN HUANG, and YONG-QI LIANG. "FUZZY EXTREME LEARNING MACHINE FOR A CLASS OF FUZZY INFERENCE SYSTEMS." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 21, supp02 (October 31, 2013): 51–61. http://dx.doi.org/10.1142/s0218488513400151.
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Recently an Online Sequential Fuzzy Extreme Learning (OS-Fuzzy-ELM) algorithm has been developed by Rong et al. for the RBF-like fuzzy neural systems where a fuzzy inference system is equivalent to a RBF network under some conditions. In the paper the learning ability of the batch version of OS-Fuzzy-ELM, called as Fuzzy-ELM is further evaluated to train a class of fuzzy inference systems which can not be represented by the RBF networks. The equivalence between the output of the fuzzy system and that of a generalized Single-Hidden Layer Feedforward Network as presented in Huang et al. is shown first, which is then used to prove the validity of the Fuzzy-ELM algorithm. In Fuzzy-ELM, the parameters of the fuzzy membership functions are randomly assigned and then the corresponding consequent parameters are determined analytically. Besides an input variable selection method based on the correlation measure is proposed to select the relevant inputs as the inputs of the fuzzy system. This can avoid the exponential increase of number of fuzzy rules with the increase of dimension of input variables while maintaining the testing performance and reducing the computation burden. Performance comparison of Fuzzy-ELM with other existing algorithms is presented using some real-world regression benchmark problems. The results show that the proposed Fuzzy-ELM produces similar or better accuracies with a significantly lower training time.
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Luo, Yao, Hui Shi, and Weiqiang Wang. "Response of extreme significant wave height to climate change in the South China Sea and northern Indian Ocean." Aquatic Ecosystem Health & Management 24, no. 3 (July 1, 2021): 103–10. http://dx.doi.org/10.14321/aehm.024.03.12.
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Abstract The frequency of extreme wave events is increasing with climate change. The temporal and spatial variations of extreme wave height affect both human livelihood and the usage of ocean resources. The South China Sea and northern Indian Ocean both support coastal communities of high population density, with varied terrain structures and extreme wind and wave systems. This study focuses on the temporal and spatial variations of the extreme significant wave height in the South China Sea and northern Indian Ocean. Using nonstationary generalized extreme value analysis, trends for a 100-year return period of significant wave height were obtained for both. The most rapid increase in the 100-year return was found to be 0.015 m yr-1 in the northern South China Sea and in the Arabian Sea; however, the 100-year return significant wave height fell in the mouth of the Bay of Bengal. After analyzing the possible causes and influence factors, we found that the increase in significant wave height in the northern South China Sea was dominated by local wind-waves and similarly, the Arabian Sea was affected by swell. The NINO3.4 index shows good correlation with the significant wave height in the northern South China Sea because typhoons are related to NINO3.4 in this area. The trends of the extreme wave height in the Arabian Sea and southern Bay of Bengal have good correlations with the South Asian summer monsoon index.
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Magazù, S., and F. Migliardo. "Fragility of Bioprotectant Glass-Forming Systems in Extremophiles." Journal of Atomic, Molecular, and Optical Physics 2009 (June 4, 2009): 1–9. http://dx.doi.org/10.1155/2009/638063.
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A central issue in the adaptation of proteins and enzymes to extreme conditions is the conservation of their functional state, which is characterized by a well-balanced compromise of stability and flexibility. In this review work an overview of elastic neutron scattering (ENS) findings on a class of bioprotectant glass-forming systems, such as trehalose and its homologous (maltose and sucrose) water mixtures, is presented as a function of temperature and concentration. ENS, in fact, allows to determine some remarkable quantities in order to characterize the correlation among dynamical properties, the flexibility and fragility of biomolecules. The experimental results have pointed out a dynamical transition, which shows a crossover in molecular fluctuations between harmonic and anharmonic dynamical regimes. The ENS findings allow to characterize both the trehalose rigidity and flexibility, which are strictly connected to its superior bioprotective effectiveness. In this frame the lowest flexibility and fragility character of trehalose/H2O mixture with respect to maltose and sucrose/H2O mixtures indicate a better attitude to encapsulate biostructures in more rigid and temperature insensitive structures in approaching the glass transition.
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Bué, Isabel, Álvaro Semedo, and João Catalão. "Evaluation of HF Radar Wave Measurements in Iberian Peninsula by Comparison with Satellite Altimetry and in Situ Wave Buoy Observations." Remote Sensing 12, no. 21 (November 4, 2020): 3623. http://dx.doi.org/10.3390/rs12213623.
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The skills of CODAR SeaSonde coastal high-frequency radars (HFR) located in the West Iberian Peninsula on measuring wave parameters are compared to in situ (buoy) and satellite altimeters (SA) wave observations. Significant wave heights (SWH), wave periods, and wave directions are compared over a time window of 36-months, from January 2017 to December 2019. The ability of HFR systems to capture extreme wave events is also assessed by comparing SWH measurements during the Emma storm, which hit the Iberian Peninsula in March 2018. The analysis presented in this study shows a slight overestimation of the SWH by the HFR systems. Comparisons with in situ observations revealed correlation coefficients (R) of the order of 0.69–0.87, biases below 0.60 m, root-mean-squared errors (RMSE) between 0.89 m to 1.18 m, and a slope regression between 1.01 and 1.26. Using buoy observations as reference ground truth, the comparisons with SA revealed Rs higher than 0.94, biases under 0.19 m, and RMSEs between 0.17 m and 0.42 m. Since in situ observations do not overlap all the HFR range cells (RC), and its correlation coefficients with SA have shown good agreement (R > 0.94), Sentinel-3 SA (SRAL) SWH measurements are further used for the validation of the HFR systems SWH observations. The comparison between the HFR and the SA collocated SWH observations allowed the evaluation of the ability of the radars to retrieve wave data as a function of the distance to the coast, particularly during extreme wave events. The comparison of the lower frequency (4.86 MHz) HFR coastal radars with the SA measurements showed an R of 0.94–0.99, a negative but reduced bias (−0.37), and an RMSE of 0.53 m. The higher frequency HFR systems (12–13.5 MHz) showed R between 0.53 and 0.82, and a clear overestimation of the SWH by the HFR sites.
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Fang, Jiayi, Thomas Wahl, Jian Fang, Xun Sun, Feng Kong, and Min Liu. "Compound flood potential from storm surge and heavy precipitation in coastal China: dependence, drivers, and impacts." Hydrology and Earth System Sciences 25, no. 8 (August 12, 2021): 4403–16. http://dx.doi.org/10.5194/hess-25-4403-2021.
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Abstract. The interaction between storm surge and concurrent precipitation is poorly understood in many coastal regions. This paper investigates the potential compound effects from these two flooding drivers along the coast of China for the first time by using the most comprehensive records of storm surge and precipitation. Statistically significant dependence between flooding drivers exists at the majority of locations that are analysed, but the strength of the correlation varies spatially and temporally and depending on how extreme events are defined. In general, we find higher dependence at the south-eastern tide gauges (TGs) (latitude < 30∘ N) compared to the northern TGs. Seasonal variations in the dependence are also evident. Overall there are more sites with significant dependence in the tropical cyclone (TC) season, especially in the summer. Accounting for past sea level rise further increases the dependence between flooding drivers, and future sea level rise will hence likely lead to an increase in the frequency of compound events. We also find notable differences in the meteorological patterns associated with events where both drivers are extreme versus events where only one driver is extreme. Events with both extreme drivers at south-eastern TG sites are caused by low-pressure systems with similar characteristics across locations, including high precipitable water content (PWC) and strong winds that generate high storm surge. Based on historical disaster damages records of Hong Kong, events with both extreme drivers account for the vast majority of damages and casualties, compared to univariate flooding events, where only one flooding driver occurred. Given the large coastal population and low capacity of drainage systems in many Chinese urban coastal areas, these findings highlight the necessity to incorporate compound flooding and its potential changes in a warming climate into risk assessments, urban planning, and the design of coastal infrastructure and flood defences.
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Sunyer, M. A., H. J. D. Sørup, O. B. Christensen, H. Madsen, D. Rosbjerg, P. S. Mikkelsen, and K. Arnbjerg-Nielsen. "On the importance of observational data properties when assessing regional climate model performance of extreme precipitation." Hydrology and Earth System Sciences Discussions 10, no. 6 (June 3, 2013): 7003–43. http://dx.doi.org/10.5194/hessd-10-7003-2013.
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Abstract. In recent years, there has been an increase in the number of climate studies addressing changes in extreme precipitation. A common step in these studies involves the assessment of the climate model performance. This is often measured by comparing climate model output with observational data. In the majority of such studies the characteristics and uncertainties of the observational data are neglected. This study addresses the influence of using different observational datasets to assess the climate model performance. Four different datasets covering Denmark using different gauge systems and comprising both networks of point measurements and gridded datasets are considered. Additionally, the influence of using different performance indices and metrics is addressed. A set of indices ranging from mean to extreme precipitation properties is calculated for all the datasets. For each of the observational datasets, the RCMs are ranked according to their performance using two different metrics. These are based on the error in representing the indices and the spatial correlation. In comparison to the mean, extreme precipitation indices are highly dependent on the spatial resolution of the observations. The spatial correlation also shows differences between the observational datasets. These differences have a clear impact on the ranking of the climate models, which is highly dependent on the observational dataset, the index and the metric used. The results highlight the need to be aware of the properties of observational data chosen in order to avoid overconfident and misleading conclusions with respect to climate model performance.
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Yeromina, Nataliia, Volodymyr Kurban, Serhii Mykus, Oleksandr Peredrii, Oleksandr Voloshchenko, Vitalii Kosenko, Vasyl Kuzavkov, Oleh Babeliuk, Maksym Derevianko, and Hennadii Kovalov. "The Creation of the Database for Mobile Robots Navigation under the Conditions of Flexible Change of Flight Assignment." International Journal of Emerging Technology and Advanced Engineering 11, no. 5 (May 20, 2021): 37–44. http://dx.doi.org/10.46338/ijetae0521_05.
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The necessity to find a rational way of creating a database regarding the sighting surface taking into consideration the features of construction and functioning of correlation-extreme navigation systems (CENS) of aerial mobile robots (MR), including in particular the conditions of flexible change of flight assignment, is shown in the article. It is proposed to use invariants, which have been obtained based on a correlation analysis of the scene according to the brightness index with the subsequent and allowing to form selective images, as a database information content. The results of the evaluation of the quality of formed selective reference image (RI) for scenes with various object impletion under conditions of limitations in time and number of calculations are given
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Chan, Alan H. S., and Alan J. Courtney. "Revising and Validating the Random Search Model for Competitive Search." Perceptual and Motor Skills 87, no. 1 (August 1998): 251–60. http://dx.doi.org/10.2466/pms.1998.87.1.251.
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A random search model was fit to a total of 2592 visual search times on a single-target detection task. By using a competing homogeneous background and uniform stimulus material, specifying viewing distance, controlling the presentation of search task material, and eliminating some options for extreme search strategies, very high correlation coefficients were found when a random search model was fit to both the individual data and to pooled data. A response time parameter was incorporated into the traditional random-search model and very good predictions of search performance were obtained.
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García-Cerezo, Álvaro, Luis Baringo, and Raquel García-Bertrand. "Representative Days for Expansion Decisions in Power Systems." Energies 13, no. 2 (January 10, 2020): 335. http://dx.doi.org/10.3390/en13020335.
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Short-term uncertainty needs to be properly modeled when analyzing a planning problem in a power system. Since the use of all available historical data may lead to problems of computational intractability, clustering algorithms may be applied in order to reduce the computational effort without compromising accurate representation of historical data. In this paper, we propose a modified version of the traditional K-means method, seeking to represent the maximum and minimum values of input data, namely, electricity demand and renewable production in several locations of a power system. Extreme values of these parameters must be represented as they are high-impact decisions that are taken with respect to expansion and operation. The method proposed is based on the K-means algorithm, which represents the correlation between demand and wind-power production. The chronology of historical data, which influences the performance of some technologies, is characterized through representative days, each made up of 24 operating conditions. A realistic case study, applying representative days, analyzes the generation and transmission expansion planning of the IEEE 24-bus Reliability Test System. Results show that the proposed method is preferable to the traditional K-means technique.
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MEDINA, LUIS FERNANDO. "Party Discipline with Legislative Initiative." British Journal of Political Science 36, no. 1 (December 8, 2005): 113–32. http://dx.doi.org/10.1017/s0007123406000068.
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This article analyses the role of parties in political systems with legislative initiative. The model explicitly takes into account the multi-district nature of elections so that voters recognize that they are not voting for a policy but for members of a policy-making body. In this setting, parties can attain their ideological goals without resorting to extreme discipline of their members in the legislature. With respect to the electorate, although voters are endowed with perfect information about their candidates' ideological stance, this model explains how the legislature will display correlation across ideology and party, a feature often attributed to imperfect information.
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Bodini, A., and Q. A. Cossu. "Vulnerability assessment of Central-East Sardinia (Italy) to extreme rainfall events." Natural Hazards and Earth System Sciences 10, no. 1 (January 14, 2010): 61–72. http://dx.doi.org/10.5194/nhess-10-61-2010.
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Abstract. In Sardinia (Italy), the highest frequency of extreme events is recorded in the Central-East area (3–4 events per year). The presence of high and steep mountains near the sea on the central and south-eastern coast, causes an East-West precipitation gradient in autumn especially, due to hot and moist currents coming from Africa. Soil structure and utilization make this area highly vulnerable to flash flooding and landslides. The specific purpose of this work is to provide a description of the heavy rainfall phenomenon on a statistical basis. The analysis mainly focuses on i) the existence of trends in heavy rainfall and ii) the characterization of the distribution of extreme events. First, to study possible trends in extreme events a few indices have been analyzed by the linear regression test. The analysis has been carried out at annual and seasonal scales. Then, extreme values analysis has been carried out by fitting a Generalized Pareto Distribution (GPD) to the data. As far as trends are concerned, different results are obtained at the two temporal scales: significant trends are obtained at the seasonal scale which are masked at the annual scale. By combining trend analysis and GPD analysis, the vulnerability of the study area to the occurrence of heavy rainfall has been characterized. Therefore, this work might support the improvement of land use planning and the application of suitable prevention systems. Future work will consider the extension of the analysis to all Sardinia and the application of statistical methods taking into account the spatial correlation of extreme events.
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Persinger, M. A. "Paranormal and Religious Beliefs May Be Mediated Differentially by Subcortical and Cortical Phenomenological Processes of the Temporal (Limbic) Lobes." Perceptual and Motor Skills 76, no. 1 (February 1993): 247–51. http://dx.doi.org/10.2466/pms.1993.76.1.247.
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The vectorial hemisphericity concept predicts that endorsements of beliefs in paranormal phenomena are associated with elevated subcortical (complex partial epileptic-like signs) temporal lobe experiences while endorsements of religious beliefs are associated with experiences of the right (cortical) hemispheric equivalent (the sensed presence) of the linguistic sense of self. Partial correlation analyses, which removed the expected shared variance, supported this hypothesis for 400 men and 400 women; religious affiliation did not contribute any statistically significant influence. However, agreements with extreme religious beliefs, such as killing others in God's name, were associated with weekly church attendance and were primarily endorsed by men but not by women.
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Cao, Li, Yong Cai, and Yinggao Yue. "Data Fusion Algorithm for Heterogeneous Wireless Sensor Networks Based on Extreme Learning Machine Optimized by Particle Swarm Optimization." Journal of Sensors 2020 (August 13, 2020): 1–17. http://dx.doi.org/10.1155/2020/2549324.
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Data fusion can reduce the data communication time between sensor nodes, reduce energy consumption, and prolong the lifetime of the network, making it an important research focus in the field of heterogeneous wireless sensor networks (HWSNs). Normal sensor nodes are susceptible to external environmental interferences, which affect the measurement results. In addition, raw data contain redundant information. The transmission of redundant information consumes excess energy, thereby reducing the lifetime of the network. We propose a data fusion method based on an extreme learning machine optimized by particle swarm optimization for HWSNs. The spatiotemporal correlation between the data of the HWSNs is determined, and the extreme learning machine method is used to process the data collected by the sensor nodes in the hierarchical routing structure of the HWSN. The particle swarm optimization algorithm is used to optimize the input weight matrix and the hidden layer bias of the extreme learning machine. An output weight matrix is created to reduce the number of hidden layer nodes and improve the generalization ability of the model. The data fusion model fuses the original data collected by the sensor nodes. The simulation results show that the proposed algorithm reduces network energy consumption and improves the lifetime of the network, the efficiency of data fusion, and the reliability of data transmission compared with other data fusion methods.
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Rajaji, V. Dega, and K. Chandra Sekhar. "A GA trained ANN model for maximum power point tracking in solar photo voltaic systems." International Journal of Engineering & Technology 7, no. 1.9 (March 1, 2018): 294. http://dx.doi.org/10.14419/ijet.v7i1.9.10383.
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Sunlight based vitality is one of the imperative segment of sustainable power source assets and reaping of sun oriented vitality is an actually difficult assignment. Sunlight based PV cells display non liner conduct and their execution is affected by an assortment of components. Fluctuating insolation and temperature assumes a critical part in characterizing the working purpose of the PV cell. Most extreme Power Point Tracking (MPPT) calculations are important to amplify the yield control. The target of getting MPP in PV frameworks is to manage the real working voltage of PV boards. The fundamental reason for acquiring MPP in PV frameworks is to direct the real working voltage of PV boards. In this paper a Genetic Algorithm (GA) –Artificial Neural Network (ANN) MPPT approach is presented. GA is employed to adaptively change the weights during the course of ANN training. The proposed approach is validated by comparing its performance against a data set which contains voltages forecast by ANN approach, Adaptive Neuro Fuzzy (ANFIS) approach and reference voltage obtained through mathematical modeling. The results demonstrate the suitability of the proposed approach in maximum power point tracking through its better performance when compared to the other two approaches. Pearson product-moment correlation has also been calculated to compare the correlation between the predicted voltage and the reference voltage.
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Gill, Richard David. "The Triangle Wave Versus the Cosine: How Classical Systems Can Optimally Approximate EPR-B Correlations." Entropy 22, no. 3 (February 29, 2020): 287. http://dx.doi.org/10.3390/e22030287.
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The famous singlet correlations of a composite quantum system consisting of two two-level components in the singlet state exhibit notable features of two kinds. One kind are striking certainty relations: perfect anti-correlation, and perfect correlation, under certain joint settings. The other kind are a number of symmetries, namely invariance under a common rotation of the settings, invariance under exchange of components, and invariance under exchange of both measurement outcomes. One might like to restrict attention to rotations in the plane since those are the ones most commonly investigated experimentally. One can then also further distinguish between the case of discrete rotations (e.g., only settings which are a whole number of degrees are allowed) and continuous rotations. We study the class of classical correlation functions, i.e., generated by classical physical systems, satisfying all these symmetries, in the continuous, planar, case. We call such correlation functions classical EPR-B correlations. It turns out that if the certainty relations and rotational symmetry holds at the level of the correlations, then rotational symmetry can be imposed “for free” on the underlying classical physical model by adding an extra randomisation level. The other binary symmetries are obtained “for free”. This leads to a simple heuristic description of all possible classical EPR-B correlations in terms of a “spinning bi-coloured disk” model. We deliberately use the word “heuristic” because technical mathematical problems remain wide open concerning the transition from finite or discrete to continuous. The main purpose of this paper is to bring this situation to the attention of the mathematical community. We do show that the widespread idea that “quantum correlations are more extreme than classical physics would allow” is at best highly inaccurate, through giving a concrete example of a classical correlation which satisfies all the symmetries and all the certainty relations and which exceeds the quantum correlations over a whole range of settings. It is found by a search procedure in which we randomly generate classical physical models and, for each generated model, evaluate its properties in a further Monte-Carlo simulation of the model itself.
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Yongsheng, Deng, Jiao Fengshun, Zhang Jie, and Li Zhikeng. "A Short-Term Power Output Forecasting Model Based on Correlation Analysis and ELM-LSTM for Distributed PV System." Journal of Electrical and Computer Engineering 2020 (June 29, 2020): 1–10. http://dx.doi.org/10.1155/2020/2051232.
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Accurate short-term power output forecasting results are conducive to reducing the scheduling difficulty of grid-connected operation of distributed photovoltaic (PV) systems, thus improving the safety and stability of power grid operation. In this paper, a one-day-ahead short-term power output forecasting model based on correlation analysis and combination algorithms for distributed PV system is proposed to solve the problems within the current methods. Firstly, the basic information of distributed PV system is introduced, and the main influence factors affecting the power output of distributed PV system are determined. Secondly, the influence factors with higher correlation with PV output are selected by Spearman rank-order correlation coefficient (SROCC) analysis in multiple timescales. Then, based on the multimodel univariate extreme learning machine (ELM) submodel and the single-model multivariate long short-term memory (LSTM) submodel, the ELM-LSTM model is established. The case study analysis based on the actual data indicates that the ELM-LSTM forecasting model proposed in this paper has higher forecasting accuracy than the traditional forecasting methods.
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Conde, Jorge, and Alejandro Bernabeu. "Non-Proportionality Indices and Error Constraint in Modal Analysis of Viscously Damped Linear Structures." Applied Sciences 11, no. 13 (June 29, 2021): 6064. http://dx.doi.org/10.3390/app11136064.
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Use of modal procedures in systems with non-proportional damping (such as structures with added viscous damping systems) results in response errors, shown in this study to depend on dissimilar and often conflicting conditions for different variables and stories; thus, it is not possible to propose simple rules based on structural or damping properties to limit the error in a global way. However, four existing indices (originally proposed to measure damping non-proportionality) present a positive correlation with the extreme errors in modal procedures for all variables and stories. Thus, limiting the index value is a sufficient condition to keep the error in all variables within a given threshold. For practical application, limit values for these indices are tabulated as a function of error and can be used as an acceptance criterion for the validity of modal procedures.
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Simões, André Luiz Andrade, Harry Edmar Schulz, and Lafayette Dantas da Luz. "Dimensionless formulation for human stability in open flows." RBRH 21, no. 4 (September 15, 2016): 666–73. http://dx.doi.org/10.1590/2318-0331.011616019.
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ABSTRACT The stability of humans partially immersed in risky open water flows, resulting from urban flooding caused for example by dam breaks, or failures in drainage systems, or natural extreme events, is a topic of increasing interest because it involves the human safety in an environment that is more and more subjected to extreme events of hydraulic nature. The studies in this field of the applied fluid mechanics generally present equations that handle the results through dimensional quantities. These results were generally obtained in specific experiments for the evaluation of the stability of models of the human body. Intending to advance in the direction of a more general formulation, a dimensional analysis for the problem of human stability in open flows is presented here, showing dimensionless groups that represent the mentioned problem. Equations using these nondimensional groups were then developed using statistical analyses and approximations based on principles of physics and on data of the human body. The results obtained with the proposed methodology are of very good quality, presenting high correlation coefficients and good agreement between measured and calculated data.
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Müller, Markus G., and Hanspeter Huber. "Linear Scaling with Cluster Size for Calculations of NMR Properties in Liquids." Collection of Czechoslovak Chemical Communications 68, no. 12 (2003): 2292–96. http://dx.doi.org/10.1135/cccc20032292.
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It is shown for liquid water that the contributions of the solvent molecules to the NMR chemical shielding of a proton in the solute molecule is approximately pair-additive. This leads to linear scaling in the computational effort with cluster size if the cluster method is applied. Alternatively, a pair chemical shielding surface, in analogy to the pair potential surface, can be calculated in advance of the simulation. Its analytical fit can be coded into the simulation program to be easily evaluated any time during the simulation, e.g. to get time correlation functions. As water is an extreme case, it is assumed that for other systems an even better additivity might be found.
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Püski, J., S. Bozó, I. Györkös, A. Gáspárdy, and E. Szücs. "Vergleich von vier Merkmalen innerhalb der 50-Punkte-Exterieurbeurteilung mit den erfassten Körpermaßen bei Holstein-Friesian Kühen." Archives Animal Breeding 44, no. 1 (October 10, 2001): 33–46. http://dx.doi.org/10.5194/aab-44-33-2001.
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Abstract. Title of the paper: Comparison of the conformation scoring and the body measurement based on four linear traits of Holstein Friesian cows The goal was evaluate the similarity of the body scoring System and the body measurement kept generally for the best objective method. The target-traits (withers height, body depth, rump width at the gluteal tuberosity and body capacity) of Holstein Friesian heifers were taken down. Three-three groups (−extreme, medium, +extreme) based on the Standard deviation of the body measurements were created and compared in each traits, as well as phenotypic relationships (regression and correlation) were calculated. Taking the relationships into consideration it appeared that the body measurements do not stand in such a close connection with each other than it is suggested by the scoring. The pair-wise correlation coefficients between the values of the same traits taken down by scoring and measuring Systems can by seen as low figures (r = 0.71, 0.50, 0.43 and 0.59, respectively) since we have the same traits. The partial correlation coefficients are even more less than the pair-wise correlation coefficients, and statistically confirmed only by the height at wither. Except the height at wither, there were no demonstrable connections in the regression of the same traits, just then, exclusively the true height at wither influenced the classifier during the scoring of all the traits. The differences between the type groups were smaller in each traits estimated by scoring. From the analysis of the type groups it is obvious that the similarity of the two methods is the biggest in the height at wither. In the case of body depth, rump width and body capacity the classifier can distinguish only the "very little" and "very large" animals from the judged population while the intermediate types remained unrecognised. The average value of the individual identity between the two typing method was around 35%.
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Vera, Wilfredo, and Martin S. Fiebert. "Validity of an Instrument Measuring Male Attitudes: The Traditional-Liberated Content Scale." Perceptual and Motor Skills 65, no. 2 (October 1987): 437–38. http://dx.doi.org/10.2466/pms.1987.65.2.437.
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This study was undertaken to investigate the validity of two factors in The Traditional-Liberated Content Scale, an instrument which shows promise in assessing some major dimensions of men's attitudes. Scores were compiled from the ratings made by 83 college undergraduate men and on a short form of the Brannon Masculinity Scale. Subjects also rated the meaning of four concepts representing major areas of change for the male sex-role. Different bipolar-adjective scales were used to rate these concepts. As indicative of the concurrent validity, each factor had a modest, but statistically significant correlation with scores on the Brannon Masculinity Scale. Support for construct validity also was obtained as subjects with extreme scores on these two factors differed in their ratings of two of the four concepts.
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Louk, Maya Hilda Lestari, and Bayu Adhi Tama. "Revisiting Gradient Boosting-Based Approaches for Learning Imbalanced Data: A Case of Anomaly Detection on Power Grids." Big Data and Cognitive Computing 6, no. 2 (April 16, 2022): 41. http://dx.doi.org/10.3390/bdcc6020041.
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Gradient boosting ensembles have been used in the cyber-security area for many years; nonetheless, their efficacy and accuracy for intrusion detection systems (IDSs) remain questionable, particularly when dealing with problems involving imbalanced data. This article fills the void in the existing body of knowledge by evaluating the performance of gradient boosting-based ensembles, including gradient boosting machine (GBM), extreme gradient boosting (XGBoost), LightGBM, and CatBoost. This paper assesses the performance of various imbalanced data sets using the Matthew correlation coefficient (MCC), area under the receiver operating characteristic curve (AUC), and F1 metrics. The article discusses an example of anomaly detection in an industrial control network and, more specifically, threat detection in a cyber-physical smart power grid. The tests’ results indicate that CatBoost surpassed its competitors, regardless of the imbalance ratio of the data sets. Moreover, LightGBM showed a much lower performance value and had more variability across the data sets.
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Dunaevskaya, K. V., L. V. Kiselev, and V. B. Kostousov. "Study of a Method for Calculating the Current Accuracy In Map-Aided Navigation Problem." Giroskopiya i Navigatsiya 29, no. 1 (2021): 52–69. http://dx.doi.org/10.17285/0869-7035.0056.
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The paper studies a previously proposed method for calculating the current accuracy characteristics of a correlation-extreme search algorithm for solving the map-aided navigation problem. The proposed method is based on the analysis of the ratio of the extreme values of the functional used in the search algorithm for comparing the measured field fragment, and the fragments obtained from a reference map, and on determining the diameter of the set of the given level for this functional. The study is carried out using an example of three spatial geophysical fields: the sea depth field, the field of gravity anomalies, and the anomalous magnetic field; it is focused on their application for underwater vehicle navigation. The specific features of the information and measurement systems used in the survey of these fields, done by means of an underwater robot are described, as well as the procedure simulating the mapping process taking these features into account. The results of computer experiments on comparison of the proposed method for calculating the current accuracy and the method used in the Bayesian algorithm for solving the navigation problem are presented.
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Shen, Jue, Shaoyu Lu, Tianyue Sun, and Yan Feng. "Elastic–plastic transition of compressional shocks in a perfect 2D Yukawa crystal." Physics of Plasmas 29, no. 5 (May 2022): 053701. http://dx.doi.org/10.1063/5.0088820.
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Molecular dynamical simulations are performed to systematically investigate the elastic–plastic transition of compressional shocks in a perfect two-dimensional Yukawa crystal. Following the tradition in the theory of elasticity, a stress tensor is used to characterize the state of stress of the simulated systems, and then the variation of the maximum shear stress in the postshock region is precisely obtained. It is found that, as the compression level gradually increases in the 2D Yukawa crystal, the maximum shear stress first increases linearly with the compressional speed until it reaches its extreme value, then decreases drastically to a much lower level. This obtained extreme value of the maximum shear stress is just at the elastic–plastic transition point, corresponding to one-half of the yield stress, which represents the ability to resist the maximum applied shear for the simulated Yukawa crystal. Our calculated Voronoi diagrams and pair correlation functions in the direction perpendicular to the shock compression further confirm this elastic–plastic transition point. It is also found that the critical compressional speed of the elastic–plastic transition point increases with the coupling parameter and decreases with the screening parameter of the 2D Yukawa crystal.
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Möller, Peter, Peter Dulski, and Marco De Lucia. "REY Patterns and Their Natural Anomalies in Waters and Brines: The Correlation of Gd and Y Anomalies." Hydrology 8, no. 3 (August 6, 2021): 116. http://dx.doi.org/10.3390/hydrology8030116.
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Rare earths and yttrium (REY) distribution patterns of the hydrosphere reveal systematic correlations of Gd and Y anomalies besides the non-correlated redox-dependent Ce and Eu anomalies. Eu anomalies are inherited by dissolution of feldspars in igneous rocks, whereas Ce, Gd and Y anomalies develop in aqueous systems in contact with minerals and amorphous matter. Natural, positive Gd and Y anomalies in REY patterns characterize high-salinity fluids from the Dead Sea, Israel/Jordan, the Great Salt Lake, USA, the Aral Sea, Kazakhstan/Uzbekistan, ground- and surface water worldwide. Extreme Gd anomalies mostly originate from anthropogenic sources. The correlation of Gd and Y anomalies at low temperature in water bodies differ from geothermal ones. In nature, dynamic systems prevail in which either solids settle in water columns or water moves through permeable sediments or sedimentary rocks. In both cases, the anomalies in water develop due to repeated equilibration with solid matter. Thus, these anomalies provide information about the hydrological history of seawater, fresh groundwater and continental brines. When migrating, the interaction of aqueous phases with mineral surfaces leads to increasing anomalies because the more hydrophillic Gd and Y preferentially remain in the aqueous phase compared to their nearest neighbors. The correlation coefficients between Gd and Y anomalies in groundwater is 0.5–0.9. In lakes and oceans, it is about 0.1–0.8, under anomalous conditions it can increase to 1.
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Al-Saidi, Nadia M. G., Dhurgham Younus, Hayder Natiq, M. R. K. Ariffin, M. A. Asbullah, and Z. Mahad. "A New Hyperchaotic Map for a Secure Communication Scheme with an Experimental Realization." Symmetry 12, no. 11 (November 15, 2020): 1881. http://dx.doi.org/10.3390/sym12111881.
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Using different chaotic systems in secure communication, nonlinear control, and many other applications has revealed that these systems have several drawbacks in different aspects. This can cause unfavorable effects to chaos-based applications. Therefore, presenting a chaotic map with complex behaviors is considered important. In this paper, we introduce a new 2D chaotic map, namely, the 2D infinite-collapse-Sine model (2D-ICSM). Various metrics including Lyapunov exponents and bifurcation diagrams are used to demonstrate the complex dynamics and robust hyperchaotic behavior of the 2D-ICSM. Furthermore, the cross-correlation coefficient, phase space diagram, and Sample Entropy algorithm prove that the 2D-ICSM has a high sensitivity to initial values and parameters, extreme complexity performance, and a much larger hyperchaotic range than existing maps. To empirically verify the efficiency and simplicity of the 2D-ICSM in practical applications, we propose a symmetric secure communication system using the 2D-ICSM. Experimental results are presented to demonstrate the validity of the proposed system.
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Kowalczyk, Adam, Robert Hanus, and Anna Szlachta. "Investigation of the Statistical Method of Time Delay Estimation Based on Conditional Averaging of Delayed Signal." Metrology and Measurement Systems 18, no. 2 (January 1, 2011): 335–42. http://dx.doi.org/10.2478/v10178-011-0015-3.
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Investigation of the Statistical Method of Time Delay Estimation Based on Conditional Averaging of Delayed Signal This paper presents the results of the theoretical and practical analysis of selected features of the function of conditional average value of the absolute value of delayed signal (CAAV). The results obtained with the CAAV method have been compared with the results obtained by method of cross correlation (CCF), which is often used at the measurements of random signal time delay. The paper is divided into five sections. The first is devoted to a short introduction to the subject of the paper. The model of measured stochastic signals is described in Section 2. The fundamentals of time delay estimation using CCF and CAAV are presented in Section 3. The standard deviations of both functions in their extreme points are evaluated and compared. The results of experimental investigations are discussed in Section 4. Computer simulations were used to evaluate the performance of the CAAV and CCF methods. The signal and the noise were Gaussian random variables, produced by a pseudorandom noise generator. The experimental standard deviations of both functions for the chosen signal to noise ratio (SNR) were obtained and compared. All simulation results were averaged for 1000 independent runs. It should be noted that the experimental results were close to the theoretical values. The conclusions and final remarks were included in Section 5. The authors conclude that the CAAV method described in this paper has less standard deviation in the extreme point than CCF and can be applied to time delay measurement of random signals.
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Pardo, María, Ana B. Crujeiras, María Amil, Zaida Aguera, Susana Jiménez-Murcia, Rosa Baños, Cristina Botella, et al. "Association of Irisin with Fat Mass, Resting Energy Expenditure, and Daily Activity in Conditions of Extreme Body Mass Index." International Journal of Endocrinology 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/857270.
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FNDC5/irisin has been recently postulated as beneficial in the treatment of obesity and diabetes because it is induced in muscle by exercise, increasing energy expenditure. However, recent reports have shown that WAT also secretes irisin and that circulating irisin is elevated in obese subjects. The aim of this study was to evaluate irisin levels in conditions of extreme BMI and its correlation with basal metabolism and daily activity. The study involved 145 female patients, including 96 with extreme BMIs (30 anorexic (AN) and 66 obese (OB)) and 49 healthy normal weight (NW). The plasma irisin levels were significantly elevated in the OB patients compared with the AN and NW patients. Irisin also correlated positively with body weight, BMI, and fat mass. The OB patients exhibited the highest REE and higher daily physical activity compared with the AN patients but lower activity compared with the NW patients. The irisin levels were inversely correlated with daily physical activity and directly correlated with REE. Fat mass contributed to most of the variability of the irisin plasma levels independently of the other studied parameters.Conclusion. Irisin levels are influenced by energy expenditure independently of daily physical activity but fat mass is the main contributing factor.
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Zhu, Yuan, Kun Xie, Kaan Ozbay, Fan Zuo, and Hong Yang. "Data-Driven Spatial Modeling for Quantifying Networkwide Resilience in the Aftermath of Hurricanes Irene and Sandy." Transportation Research Record: Journal of the Transportation Research Board 2604, no. 1 (January 2017): 9–18. http://dx.doi.org/10.3141/2604-02.
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In recent years, the New York City metropolitan area was hit by two major hurricanes, Irene and Sandy. These extreme weather events disrupted and devastated the transportation infrastructure, including road and subway networks. As an extension of the authors’ recent research on this topic, this study explored the spatial patterns of infrastructure resilience in New York City with the use of taxi and subway ridership data. Neighborhood tabulation areas were used as the units of analysis. The recovery curve of each neighborhood tabulation area was modeled with the logistic function to quantify the resilience of road and subway systems. Moran's I tests confirmed the spatial correlation of recovery patterns for taxi and subway ridership. To account for this spatial correlation, citywide spatial models were estimated and found to outperform linear models. Factors such as the percentage of area influenced by storm surges, the distance to the coast, and the average elevation are found to affect the infrastructure resilience. The findings in this study provide insights into the vulnerability of transportation networks and can be used for more efficient emergency planning and management.
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Zhou, Junju, Jumei Huang, Xi Zhao, Li Lei, Wei Shi, Lanying Wang, Wei Wei, Chunfang Liu, Guofeng Zhu, and Xuemei Yang. "Changes of Extreme Temperature and Its Influencing Factors in Shiyang River Basin, Northwest China." Atmosphere 11, no. 11 (October 29, 2020): 1171. http://dx.doi.org/10.3390/atmos11111171.
Full textAbstract:
The increase in the frequency and intensity of extreme weather events around the world has led to the frequent occurrence of global disasters, which have had serious impacts on the society, economic and ecological environment, especially fragile arid areas. Based on the daily maximum temperature and daily minimum temperature data of four meteorological stations in Shiyang River Basin (SRB) from 1960 to 2015, the spatio-temporal variation characteristics of extreme temperature indices were analyzed by means of univariate linear regression analysis, Mann–Kendall test and correlation analysis. The results showed that the extreme temperatures warming indices and the minimum of daily maximum temperature (TXn) and the minimum of daily minimum temperature (TNn) of cold indices showed an increasing trend from 1960 to 2016, especially since the 1990s, where the growth rate was fast and the response to global warming was sensitive. Except TXn and TNn, other cold indices showed a decreasing trend, especially Diurnal temperature (DTR) range, which decreased rapidly, indicating that the increasing speed of daily min-temperature were greater than of daily max-temperature in SRB. In space, the change tendency rate of the warm index basically showed an obvious altitude gradient effect that decreased with the altitude, which was consistent with Frost day (FD0) and Cool nights (TN10p) in the cold index, while Ice days (ID0) and Cool days (TX10p) are opposite. The mutation of the cold indices occurred earlier than the warm indices, illustrating that the cold indices in SRB were more sensitive to global warming. The change in extreme temperatures that would have a significant impact on the vegetation and glacier permafrost in the basin was the result of the combined function of different atmospheric circulation systems, which included the Arctic polar vortex, Western Pacific subtropical high and Qinghai-tibet Plateau circulation.
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Kovaleva, M. E., and V. G. Bulygina. "Physiological characteristics of regulation of emotional responses among specialists of extreme profile." Psychology and Law 7, no. 1 (2017): 53–67. http://dx.doi.org/10.17759/psylaw.2017070105.
Full textAbstract:
The results of the examination psychophysiological mechanisms of coping with emotional reactions in stressful situations of the specialists of extreme profile are presented. The integrated biofeedback protocol using various functional tests has been developed. Statistical clustering method k-means was used; validation of the differences between the resulting clusters was carried out using one-way ANOVA. The internal consistency of various indicators of the autonomic and central nervous systems was revealed by the pairwise Pearson's correlation coefficient. Target variables for the mathematical analysis were: relative powers of alpha, theta, beta 1 and beta 2 rhythms, HR, HF, LF, VLF, RR, VS, LF/HF, TP, IC, SNCA, ASV, GSR. Multiple relationships between different levels of regulation of emotional state, the flexible use of different coping strategies, the ability to create new mechanisms of regulation in accordance with the objective and high braking performance the emotional state after the termination of the stressors was detected in the group with high stress sustainability. The group with low stress sustainability has been described by the opposite pattern.