A multivariate technique named Canonical Concordance Correlation Analysis (CCCA) is introduced. In contrast to the classical Canonical Correlation Analysis (CCA) which is based on maximization of the Pearson’s correlation coefficient between th...
The major factors that determine the performance of the second-order correlation power analysis (SOCPA) include the accuracy of the power model and the correlation between the hypothetical intermediate value and preprocessed power consumption. Becaus...
Canonical correlation analysis (CCA) is a kind of a simple yet effective multiview feature learning technique. In general, it learns separate subspaces for two views by maximizing their correlations. However, there still exist two restrictions to lim...
Geologic material properties of hillslopes are inherently heterogeneous, with complex layering structures due to geological deposition processes. Lacking detailed sampling of the properties’ spatial distribution has led to the stochastic repres...
5 January 2020
Pollutant analysis and pollution source tracing are critical issues in air quality management, in which correlation analysis is important for pollutant relation modeling. A dynamic correlation analysis method was proposed to meet the real-time requir...
In recent years, the use of electroencephalography (EEG) has grown as a tool for diagnostic and brain function monitoring, being a simple and non-invasive method compared with other procedures like histological sampling. Typically, in order to extrac...
Various methods of time series analysis have been used in studies of karst hydrological systems. Among these methods, correlation and spectral analysis have had an important role. The correlation analysis most often has been based on determination of...
In recent years, increasing attention has been devoted to cryptocurrencies, owing to their great development and valorization. In this study, we propose to analyse four of the major cryptocurrencies, based on their market capitalization and data avai...
2 April 2020
The purpose of this study is to illustrate intrinsic correlations and their temporal evolution between hydro-meteorological elements by building three-element-composed system, including precipitation (P), runoff (R), air temperature (T), evaporation...
Recently, more and more countries are entering the global race for university competitiveness. On the one hand, global rankings are a convenient tool for quantitative analysis. On the other hand, their indicators are often difficult to quickly calcul...
This paper presents a correlation analysis of the structural dynamic responses and weather conditions of a railway crossing. Prior to that, the condition monitoring of the crossing as well as the indicators for crossing condition assessment are brief...
In recent years, frequent severe haze weather has formed in China, including some of the most populated areas. We found that these smog-prone areas are often relatively a “local climate” and aim to explore this series of scientific problems. This pap...
Overhung rotors are widely used in the industrial field. However, compared with normal structure rotors, the prediction and control of overhung rotors cannot achieve good performance. The work aims to investigate the dynamical behaviours of an overhu...
Multifractal Detrended Cross-Correlation Analysis (MF-DCCA) was applied to time series of global methane concentrations and remotely-sensed temperature anomalies of the global lower and mid-troposphere, with the purpose of investigating the multifrac...
This paper presents the implementation of nonlinear canonical correlation analysis (NLCCA) approach to detect steady-state visual evoked potentials (SSVEP) quickly. The need for the fast recognition of proper stimulus to help end an SSVEP task in a B...
Canonical Correlation Analysis (CCA) infers a pairwise linear relationship between two groups of random variables,
In industrial practice, excessive alarms and high alarm rates are mostly generated from unreasonable settings to variable alarm thresholds, which have become the significant causes of impact on operation stability and plant safety. A correlation degr...
KPIs (Key Performance Indicators) in distributed systems may involve a variety of anomalies, which will lead to system failure and huge losses. Detecting KPI anomalies in the system is very important. This paper presents a time series anomaly detecti...
In the large scale canonical correlation analysis arising from multi-view learning applications, one needs to compute canonical weight vectors corresponding to a few of largest canonical correlations. For such a task, we propose a Jacobi–Davids...
18 August 2016
The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility...
Pervious concrete is challenged by the inherent trade-off between permeability and mechanical strength. This study presents a systematic optimization of its mix design to achieve a balance between these properties. Single-factor experiments and an L9...
The primary motivation of this study is to develop a compound intensity measure (IM) to evaluate ground motion damage potential based on principal component analysis (PCA) and canonical correlation analysis (CCA). To illustrate this, this study exami...
To comprehensively evaluate the seismic performance of offshore bridges, a seismic risk analysis of an example bridge was developed based on improved two-dimensional (2D) seismic fragility analysis. Taking a simply-supported beam bridge in an offshor...
Alarm systems are commonly deployed in complex industries to monitor the operation status of the production process in real time. Actual alarm systems generally have alarm overloading problems. One of the major factors leading to excessive alarms is...
The present paper discusses a new approach for the experimental determination of modal parameters (resonant frequencies, modal shapes and damping coefficients) based on measured displacement values, using the non-contact optical method of digital ima...
Perca schrenkii populations are experiencing significant declines, yet comprehensive morphological studies are still lacking. Understanding the relationship between morphological traits and body weight is crucial for conservation and breeding program...
The study reported in this paper is concerned with areas related to developing methods of measuring, processing and analyzing infrasound noise caused by operation of wind farms. The paper contains the results of the correlation analysis of infrasound...
Trend analyses are common in several types of climate change studies. In many cases, finding evidence that the trends are different from zero in hydroclimate variables is of particular interest. However, when estimating the confidence interval of a s...
Metabolite differential connectivity analysis has been successful in investigating potential molecular mechanisms underlying different conditions in biological systems. Correlation and Mutual Information (MI) are two of the most common measures to qu...
Correlation-domain analysis has enabled distributed measurements of Brillouin gain spectra along optical fibers with high spatial resolution, up to millimeter-scale. The method relies on the joint modulation of counter-propagating Brillouin pump and...
Summarizing the causation of an aviation accident is beneficial for improving aviation safety. Currently, accident analysis mainly focuses on causal analysis, while giving less consideration to the correlation between accident causal factors and othe...
Associating images with sentences has drawn much attention recently. Existing methods commonly represent an image by indistinctively describing all its contents in an one-time static way, which ignores two facts that (1) the association analysis can...
In this study, we investigate multiscale auto- and cross-correlation structural characteristics of sea surface temperature (SST) variability using our new methodology, called the multifractal asymmetric cross-correlation analysis (MF-ACCA), incorpora...
10 May 2022
This study aims to investigate research trends concerning job stress among hospital nurses. Articles about job stress among hospital nurses published in English from 2008 to 2018 were searched. In the first search, 2673 articles were extracted from t...
We propose a generalized method of the canonical correlation analysis using Alpha-Beta divergence, called AB-canonical analysis (ABCA). From observations of two random variables, x ∈ RP and y ∈ RQ, ABCA finds directions, wx ∈ RP and wy ∈ RQ, such t...
A new development process for the noise, vibration, and harshness (NVH) of a vehicle is presented using data analysis and machine learning with long-term NVH driving data. The process includes exploratory data analysis (EDA), variable importance anal...
Canonical Correlation Analysis (CCA) is a classic multivariate statistical technique, which can be used to find a projection pair that maximally captures the correlation between two sets of random variables. The present paper introduces a CCA-based a...
The rare earth extraction process has significant time delay characteristics, making it challenging to identify the time delay and establish an accurate mathematical model. This paper proposes a multi-delay identification method based on improved tim...
The aim of the research was to comprehensively evaluate the impact resistance of conveyor belts. Initially, variables were identified that describe the input conditions of the experiment (weight of impacting material, impact height, type and strength...
In a closed population with a limited population size, mating of related animals is unavoidable. In this study, the genealogy data of a synthetic maternal rabbit breed called Pannon Ka were used to calculate different inbreeding coefficients. The eva...
Correlation and cross-spectral analysis of hydrographs was performed on the karst area of the mountainous section of the Kupa River in two time periods. Since there are karst aquifers in this area that is a part of strategic groundwater reserves of p...
Distributed optical fiber sensing technology has been widely applied in the areas of infrastructure health monitoring, national defense security, etc. The long-range high-spatial-resolution Brillouin optical correlation domain analysis (BOCDA) has ex...
Radar specific emitter identification (SEI) involves extracting distinct fingerprints from radar signals to precisely attribute them to corresponding radar transmitters. In view of the limited characterization of fingerprint information by single-dom...
We apply the inherent dynamic consistency of a dynamic system as the basis for correlation analysis among different variables in a system. We use network analysis to measure the correlativity of multiple variables, find the interdependence between mu...
CRYSTALS-Kyber has been standardized as a general public-key post-quantum algorithm under the name of ML-KEM after NIST released its first three final post-quantum standards in August 2024. The resilience of post-quantum cryptography to side-channel...
The investigation of the statistical links between changes in temperature and rainfall, though not widely achieved in the past, is an interesting issue because their physical interdependence is difficult to point out. Aiming at detecting possible tre...
This paper presents a method for evaluating driving behavior safety based on real-world urban driving data collected from on-road experiments. The aim of this study is to develop a comprehensive and interpretable evaluation framework to improve the i...
Structural health monitoring is a critical requirement in many composites. Numerous monitoring strategies rely on measurements of temperature or strain (or both), however these are often restricted to point-sensing or to the coverage of small areas....
The paper deals with the connection between the issue of rectification of the structural system and the corresponding experimental and related statistical analysis of stresses. The solution was demonstrated in the example of replacing the aboveground...
19 December 2018
Correlation analysis is an extensively used technique that identifies interesting relationships in data. These relationships help us realize the relevance of attributes with respect to the target class to be predicted. This study has exploited correl...
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