Canonical Correlation Method Research Articles

Correlates of multidimensional sleep in premenopausal women: The BioCycle study

PurposeTo identify sleep dimensions (characteristics) that co-occur in premenopausal women. The second aim was to examine associations between multiple dimensions of sleep and a set of demographic, lifestyle, and health correlates. The overarching goal was to uncover patterns of poor-sleep correlates that might inform interventions to improve sleep health of women in this age group. MethodsThe BioCycle Study included 259 healthy women aged 18–44y recruited between 2005 and 2007 from Western New York. Participants reported sleep data through daily diaries and questionnaires that were used to create five sleep health dimensions (duration, variability, timing, latency, and continuity). We used multivariate analysis – canonical correlation methods – to identify links among dimensions of sleep health and patterns of demographic, psychological, and occupational correlates. ResultsTwo distinct combinations of sleep dimensions were identified. The first - primarily determined by low variability in nightly sleep duration, low variability in bedtime (timing), greater nocturnal awakening, and less sleep onset latency – was distinguished from the second – primarily determined by sleep duration.The first combination of sleep dimensions was associated with older age and higher parity, fewer depressive symptoms, and higher stress level. The second combination of sleep dimensions was associated with perception of longer sleep duration as optimal, lower parity, not engaging in shift work, older age, lower stress level, higher prevalence of depressive symptoms, and White race. ConclusionAmong premenopausal women, we demonstrated distinct patterns of sleep dimensions that co-occur and vary by demographic, health, and lifestyle correlates. These findings shed light on the correlates of sleep health vulnerabilities among young women.

Challenging parents, teacher occupational stress and health in Dutch primary schools

Continual exposure to challenging behaviour, i.c. from parents, can seriously deplete the teacher’s emotional and physical resources, leading to self-doubt, loss of satisfaction from teaching, impulsivity, rigidity or feelings of anger and guilt. Research on teacher stress has largely focused on environmental and contextual factors while ignoring personality characteristics of teachers. In this study, we examined teacher’s perceptions of their own ability to handle challenging parent behaviour and to establish positive relationships as a possible influence on the quality of teacher-parent relationships. Using a canonical correlation method, we found that unsatisfied parents, overprotective parents, neglectful parents and excessively worried parents have the largest impact on teacher stress. Teachers who experience stress from challenging parent behaviour, suffer mostly from negative feelings toward parents, frustration on working with parents, loss of satisfaction with teaching and to a lesser extent health problems. The data for this research was collected in February and March 2007, amongst 212 elementary school teachers in the middle and middle-east region and urban agglomeration of Western-Holland, the Netherlands. The main aim of this research project is to identify at risk teachers (i.e. those most vulnerable to the presence of behaviourally challenging parents) so that interventions, both in initial teacher training as well as in in-service training, can be applied to help them develop adequate attitudes and coping skills.

The Use of Chosen Physicochemical Indicators for Estimation of Pork Meat Quality

The present work aimed to estimate the usefulness and effectiveness of selected physicochemical indicators in the evaluation of meat quality as well as culinary and processing value using a simple and canonical phenotypic correlation method. Studies were carried out in 495 porkers. The most relationships were obtained for the adenosine triphosphate (ATP) breakdown indicator (R1), electrical conductivity (EC) and glycolytic potential (GP) with meat quality traits that are non-diagnostic criteria, i.e., lipids and protein content, water holding capacity (WHC), technological yield (TY), drip loss (DL) and meat tenderness (MT). The results of this study indicate that about 62% of the variability in meat quality is the result of the initial level of glycogen in muscle tissue. The strong relationship between EC2 and pH24 (acidity of the muscle tissue at 24 h after slaughter) parameters and a wide spectrum of traits of meat quality (sets covering the parameters of the culinary and processing quality of meat and indicating the volume of drip loss), as well as with the pH1 and R1 criteria confirms the possibility to perform a quick and cheap ‘on line’ classification of qualitative meat properties in meat processing plants.

Determination of Impact Size by Canonic Correlation Analysis of the Factors Affecting the Buying or Selling Agricultural Lands

The aim of this study is to determine the relationship between the influencing factors in the data set created with the help of canonical correlation in the factors affecting the purchase or sale of agricultural lands in certain neighborhoods in the Dulkadiroğlu district of Kahramanmaraş province and the most effective factor or factors compared to the others. For this, a survey was conducted with the parcel owners in the determined neighborhoods and a data set of 1000 people was created. As a result of the data obtained, the first data set of the study, in which the canonical correlation method was used, was the slope and irrigation status of the land, the average productivity rate of the land, and the presence of tractors and equipment used in the land, among the factors affecting the purchase or sale of agricultural lands; land parcel size, land purchase or sale price and for what purpose the land was bought or sold were also the second data set. The rate of canonical correlation coefficient in the data sets created according to the estimation results was found to be 40.32%. In the data set we compared, the average productivity of the land was determined in the first data set with the highest effect, while in the second data set it was determined as the purpose for which the land was bought or sold

Analysis of Cylinder Drying Intensity of Cut Tobacco Based on Enthalpy Method

Cylinder drying of cut tobacco is one of the key processing technologies in cigarette manufacturing. And complex mass transfer and heat transfer phenomena were involved. In this paper, a thermodynamic model have been built for cut tobacco during cylinder drying process. The relationship of different process parameters and thermodynamic data were analyzed by canonical correlation method, including amount of heat Qv produced in moisture evaporation of cut tobacco, amount of heat Qs produced in temperature increase of cut tobacco, total amount of heat Q and thermal efficiency coefficient η. The results showed that the thermodynamic model explained the actual cut tobacco heating and heat distribution well in the cylinder drying process. The variation coefficients of the four thermodynamic parameters of cut tobacco under the same processing conditions were all less than 5.0%. It is proved that the thermodynamic model established during cylinder drying process of cut tobacco is feasible.

Identifying potential adaptive SNPs within combined DNA sequences in Genus Crocus L. (Iridaceae family): A multiple analytical approach

The genus Crocus L. of Iridaceae family contains about 160 species and is considered as a complex group of plant taxa with regard to evolutionary and phylogenetic events. Inter-specific hybridization and gene flow contribute to species genetic homogeneity in one hand and high within species genetic variability and species genetic content overlaps caused species resolution a problem. In spite of extensive molecular phylogenetic studies in this genus, nothing is known about DNA sequences or Single nucleotide polymorphisms (SNPs) which are of adaptive nature. Moreover, nothing is known about which geographical or environmental factors plays role in species local adaptation and speciation events within Crocus L. genus. Therefore, the present study was conducted to answer the above said questions. We used a combined molecular data set of internal transcribed spacer (ITS) nuclear gene and trnL-F intergenic spacer (trnL-F) sequences of chloroplast genome. A multiple analytical method of Canonical correlation (CCA), Redundency analysis (RDA), and Latent Factor Mixed Model (LFMM)identified a few potential adaptive SNPs. Moreover, population criterions like Tajimas’ D, molecular clock test, as well as skyline-plot revealed a smooth and continuous genetic changes for most of the Crocus species, but the occurrence of a sudden deep nucleotide substitution for Crocus taxa of Iran. The impact of latitude was significantly higher on nucleotide changes compared to that of longitudinal distribution of Crocus species.

Conflict of Ukrainian Generations X and Y: Ways to overcome it in the context of the war in Ukraine

In the conditions of war, the problem of maintaining a comfortable psychological climate in professional teams and society in general is acutely felt because Ukrainians are in a depressed psychological state. Conflicts among people of different ages are also escalating, as representatives of the baby boomer generation are gradually being replaced by Generation Y, and therefore most Ukrainian companies are teams of representatives of Generations X and Y. The purpose of this study is to find ways to overcome the problem of conflict between different generations. Among the key scientific methods of this study is M. Rokeach’s model, which was used to rank the terminal and instrumental values of representatives of Ukrainian generations X and Y, and the method of canonical correlations, used for comparative analysis of the value structure of the analysed generations. The main results of the study indicate that the aggravation of relations and the emergence of misunderstandings among Ukrainians is a consequence not only of the influence of war, but also of the conflict of the most economically active generations – X and Y. This conflict is caused by differences in the perception of life (i.e., in values), a large difference in the socio-political conditions of formation and belonging to different archetypes of generations according to the Strauss–Howe generational theory. Ukrainian generation X is a recessive generation of “nomads”, while generation Y is a dominant generation of “heroes”. The results of a comparative analysis of the dominant terminal and instrumental values of these generations indicated that 50% of the dominant values are common terminal and only 33% are common instrumental. It was found that the Ukrainian Generation X has more post-materialistic values, while Generation Y prefers materialistic values, which was a consequence of socio-political events in Ukraine, under which these generations were formed. The practical significance of the results obtained lies in the fact that the proposed recommendations for overcoming the conflict of Ukrainian Generations X and Y by factoring in the most important values for each of these generations will help not only to overcome the conflict of generations, but also to increase the effectiveness of their interaction.

IMPACT OF CHANGES IN MACROECONOMIC INDICATORS ON BANKING INDICATORS IN UKRAINE

The aim of the article is to study the mutual influence of the main performance indicators of the banking system of Ukraine and macroeconomic indicators of Ukraine at the present stage of its operation to outline the main factors that will promote the formation of a methodology for studying the essence of the basic processes in the functioning of banks, identifying obstacles to their development and developing effective mechanisms to improve their further activities. As a result of the study, the authors developed a multifactor model of the influence of factors on the performance of banks and used the method of canonical correlations to find the maximum correlations between groups of variables. There is a close correlation between the performance of banks and macroeconomic indicators of the country. The results of the canonical analysis confirmed that the relationship between the selected performance indicators and the selected determinants should be studied in terms of individual performance indicators of banks to form a system of scenarios for the development of these indicators depending on selected factors using the scenario method. The possibility of achieving positive changes in the banking system of Ukraine by influencing the resulting indicators of each of the significant equations through the management of specific significant factor variables is analyzed. Correlation-regression and scenario analysis makes it possible to state that the state policy should be pursued to manage a given set of factors that have a positive impact on banks' performance, promote bank capital growth, number of legal entities, average monthly salary, stability of the National Bank of Ukraine discount rate, etc.

Radio frequency fingerprinting feature fusion based on multi-domain discriminant kernel canonical correlation analysis

Specific emitter identification (SEI) refers to the precise identification of a specific transmitter through the extraction of hardware fingerprint information from the received signal. The majority of related research focuses on the definition and extraction of new fingerprint features, with less emphasis on the comprehensive use of existing features. Because the characteristics of different analysis domains are complementary to the description of the radio frequency fingerprint, this paper proposes a multi-domain feature fusion strategy for SEI based on multi-domain discriminant kernel canonical correlation analysis (MDKCCA), which fully exploits the complementarity between the features of different domains and combines feature tag information. MDKCCA affords multi-domain feature dimensionality reduction and fusion in a high-dimensional space.The algorithm's performance is validated on four different types of real-world data sets using eight common fingerprint features in four feature analysis domains. The results show that this method eliminates the need for manual feature optimization and can significantly reduce the dimensionality of fusion features. The recognition rate on various targets exceeds 95%, which is higher than the best single feature. It is also superior to the simple feature synthesis method based on direct cascade or PCA dimensionality reduction transformation, the neural network-based feature synthesis method, and the feature fusion method based on discriminant canonical correlation methods.

Clustering CITE-seq data with a canonical correlation-based deep learning method.

Single-cell multiomics sequencing techniques have rapidly developed in the past few years. Among these techniques, single-cell cellular indexing of transcriptomes and epitopes (CITE-seq) allows simultaneous quantification of gene expression and surface proteins. Clustering CITE-seq data have the great potential of providing us with a more comprehensive and in-depth view of cell states and interactions. However, CITE-seq data inherit the properties of scRNA-seq data, being noisy, large-dimensional, and highly sparse. Moreover, representations of RNA and surface protein are sometimes with low correlation and contribute divergently to the clustering object. To overcome these obstacles and find a combined representation well suited for clustering, we proposed scCTClust for multiomics data, especially CITE-seq data, and clustering analysis. Two omics-specific neural networks are introduced to extract cluster information from omics data. A deep canonical correlation method is adopted to find the maximumly correlated representations of two omics. A novel decentralized clustering method is utilized over the linear combination of latent representations of two omics. The fusion weights which can account for contributions of omics to clustering are adaptively updated during training. Extensive experiments over both simulated and real CITE-seq data sets demonstrated the power of scCTClust. We also applied scCTClust on transcriptome–epigenome data to illustrate its potential for generalizing.

Assessment of the relationship of macroeconomic indicators of the country by the method of canonical correlations

Assessment of the relationship of macroeconomic indicators of the country by the method of canonical correlations

Educational Reform to Correct the Past: Namibian Evidence

This paper used graduation statistics of the Namibian secondary higher education over two decades to determine linkages to human capital of the youth and its multiplication into economic development. The paper assessed the effect of regional differences to show historic educational discrimination and why the education reform was required to correct the skewed past. It was hypothesized that the educational reform would result into improvements of the academic levels within the disadvantaged regions and anticipated that the correction will partly have negative effects on the previously advantaged regions. By applying panel data, the paper attempts to simultaneously address the complex relationships of development, education, and the underlying causalities within the economic system of Namibia. Concepts in the testing of socio-economic components are done by looking at confounding logics, stochastics, and the use of latent variables to determine linkages by using the canonical correlation method. This approach could be extended in future as guide for decisions on education. Our study shows that the implementation of the Namibian education reform resulted into increased enrolment numbers, but unfortunately also into the declining of academic levels, combined with the narrowing of learners’ outputs. The reform response in the previously disadvantaged regions was slower than expected. Findings of the longitudinal data show that education levels in Namibia partly contributed towards human capital formation to multiply into economic development. The study shows that the method of analyzing linkages between cause and effect by means of causality provides advantages for analysis. The results confirm findings that human capital formation has a positive effect on the country's economic status, but for efficacy analysis of policy, we need regional information.

Affect, Support, and Personal Factors: Multimodal Causal Models of One-on-one Coaching

Human one-on-one coaching involves complex multimodal interactions. Successful coaching requires teachers to closely monitor students' cognitive-affective states and provide support of optimal type, timing, and amount. However, most of the existing human tutoring studies focus primarily on verbal interactions and have yet to incorporate the rich aspects of multimodal cognitive-affective experiences. Meanwhile, the research community lacks principled methods to fully exploit complex multimodal data to uncover the causal relationships between coaching supports, students' cognitive-affective experiences, and their stable individual factors. We explore an analytical framework that is explainable and amenable to incorporating domain knowledge. The proposed framework combines statistical approaches in Sparse Multiple Canonical Correlation, causal discovery, and inference methods for observations. We demonstrate this framework using a multimodal one-on-one math problem-solving coaching dataset collected in naturalistic home environments involving parents and young children. The insights derived from our analyses may inform the design of effective technology-inspired interventions that are personalized and adaptive.

Measuring entrepreneurship determinants: empirical analysis

Purpose. The aim of this article is to assess the main determinants that affect entrepreneurial activity, and also the mechanism of its regulation in five countries (Ukraine, Romania, Lithuania, Poland, Germany) during the period from 2007 to 2018. According to the purpose of the article it was empirically tested a number of hypotheses. 
 Methodology / approach. The canonical correlation method is considered as a basic method for maximum correlations between groups of variables. The group of performance indicators includes: GDP per capita, the volume of output at market prices, Global Competitiveness Index as indicators that most completely reflect the results and efficiency of entrepreneurial activity. The group of factor variables includes entrepreneurial activity determinants, which to some extent affect the change of these entrepreneurial efficiency indicators. The advantages of the proposed method is possibility to analyze the multiple relationships between business results and the determinants that determine it.
 Results. The article examines a related area of the economy, namely entrepreneurship, which is largely related to agriculture. The article gradually reveals scientific approaches to identifying the determinants of entrepreneurial activity, followed by the methodology of the conducted research, analysis of results and substantiation of hypotheses. According to the aims of the article, the authors have got the following results: 1. To analyze the entrepreneurial environment, a systematic approach must be applied whereby all the determinants of the entrepreneurial environment are interrelated and influence one another. 2. The canonical correlation method allowed to determine the system of entrepreneurial activity determinants and to confirm the statement that each country has its own system of determinants. It is justified by the heterogeneity of the studied data sample, i.e. the presence of a large difference between the numerical values of indicators for selected countries. 3. The human development determinant is the key to business development in the country. Such conclusions are made on the basis of the determinants system analysis in Germany, where indicators of business efficiency are the highest.
 Originality / scientific novelty. The article proposes a method of assessing the determinants of entrepreneurial activity through the use of the canonical correlation method. This method allows us to investigate the relationship between two sets of variables and is a generalized version of pairwise correlation, as opposed to factor analysis, which is used to establish relationships within one set of variables.
 Practical value / implications. Presented study aims to extend the empirical knowledge on the measurement of entrepreneurship at the country level and its determinants. In assessing the determinants of the entrepreneurial environment, the main causes that lead to incomplete utilization of entrepreneurial potential remain unaccounted for. Particularly practical meaning may have a thorough analysis of the determinants of entrepreneurial activity in different countries. Modern European integration aspirations of Ukraine should be provided with real socioeconomic transformations in which the development of entrepreneurial activity is key. The beginning of an effective process of forming an efficient strategic approach to creating a favourable entrepreneurial environment for every country is to study the existing experience of other countries. For Ukraine, in particular, this is the experience of the EU countries.

TARGET GROUPS FOR INCREASING FINANCIAL POTENTIAL OF THE PPP SECTORS IN ORDER TO THE GOVERNMENT’S FINANCIAL POLICY

The relationship between the financial potential of PPP sectors and financial policy has been identified, which testifies to the dependence of the overall development of public-private partnership on strategic decisions at the state level. An analysis of causal relationships with the use of the canonical correlation method has been carried out to determine the relationship between the financial potential of PPP sectors and the power of interaction with public finance policy. This allows not only to assess the prospects of the development of events in the event of a change in one of the indicators in a specific public-private partnership sector, but also in the presence of relevant mathematical and statistical models to obtain an estimate of the magnitude of secondary changes. In turn, government financial policy measures should be tailored to the current state of financial potential of public-private partnership.
 It is revealed that the financial potential of PPP sectors has a high degree of interaction with financial policy, which is confirmed by the adequacy of the system of canonical correlation equations. Ranking the indicators of the financial potential of the PPP and determining their factor load allowed formulating targets. Target indicators of public-private partnership financial potential are selected based on the sectors that are the basis for adjusting the state's financial policy in order to increase the financial potential of the public-private partnership: in the public sector - indicators of budget expenditures and the degree of subsidized equalization of regions by the state; by the private sector - indicators of the volume of return of financial resources spent on fixed assets and profitability of business entities; in the financial and credit sector, is an indicator of lending to non-financial corporations.

Використання методу головних компонент і канонічних кореляцій для виведення нових сортів культурних рослин

To develop new varieties of cultivated plants, the article proposes the use of the method of principal components at the first stage of the calculation and the method of canonical correlations at the second. Analysis of the methods of genetics and breeding on the issue of breeding new varieties of cultivated plants led to the following assumptions: a change in the basic property of any plant species is associated with the possible magnitude of the scatter of individual particular properties, and the greatest changes in the desired properties can be obtained as a result of crossing individuals that have the greatest variability of these properties. Based on this, in purposeful selection, first of all, only those features should be taken into account that show the greatest scatter in the transition from one object to another, which is possible when using the method of principal components. Principal component method is one of the main ways to reduce the dimension of data, losing the least amount of information. The problem is reduced to the classical problem of finding the eigenvalues and eigenvectors of a symmetric matrix. Among the existing approaches to solving the problem by the principal components (factors) method, this study used an approach where, to maximize a function associated with a number of additional conditions, we use the method of Lagrange multipliers. The canonical correlations method at the second stage makes it possible to find the maximum correlations between two groups of random variables, being, as it were, a generalization of the correlation analysis in the case of two sets of random variables. This dependence is determined by using new arguments - canonical values (canonical variables), calculated as linear combinations of the original features for each of the groups. Canonical values should be maximally correlated with each other, and their number is determined by the number of variables in a smaller set (if the number of variables in them is not the same). That is, at the second stage, the residence of the canonical correlations is determined for the found pairs of principal components and secondary vectors, the elements of which are the found principal components. Thus, an algorithm for directed search for pairs for crossing cultivated plants has been developed, which consists of two stages of calculation by the methods of principal components and canonical correlations.

Investigation of the Relationship between Psycho-social Factors and Psychological Symptoms by Canonic Correlation Analysis

The purpose of this research is to examine the relationships between psychosocial variables and psychological manifestations through canonical correlation analysis, a multivariate analysis technique. Analyzes were conducted on the psychosocial variables and psychological symptom levels of the students. Canonical correlation method was used in the analysis of the data. The first set (sex, department preference order, class level, f4 department satisfaction level, university satisfaction level, request to change department, order of birth, form of marriage, previous psychological help, request for psychological help, eating habits, having chronic illness, suicide, having harmful habits) was found to disclose the second set (somatization, obsessive-compulsive disorder, interpersonal sensitivity, depression, anxiety, hostility, phobic anxiety, paranoid thought, psychotic, guilt, insomnia and appetite) at 75%.

Facial image recognition for biometric authentication systems using a combination of geometrical feature points and low-level visual features

This paper proposes a method for biometric-driven facial image recognition, based on multivariate correlation analysis, which extracts geometrical feature points and low-level visual features. The low-level visual features, such as colour and texture, are extracted at local from the selected prominent regions of the facial image. The geometrical features are captured using the Active Shape Model (ASM). The colour features are extracted from the YCbCr colour model, and the autocorrelation method is deployed to extract the texture features. The extracted features are formed as a feature tensor matrix. The feature matrix of the key face image is compared to the feature matrices of the target face image that are stored in the feature vector database using the Canonical Correlation method. The correlation between the key and target feature matrices is tested, whether it is highly significant or not. If it is significantly correlated, then it is inferred that the key and target face images are the same; otherwise, it is concluded that they are different. The benchmark facial image datasets, GT, LFW, and Pointing ’04 datasets, considered for the experiments; in addition to the datasets, a facial image database has been constructed with celebrities on our interest which has also been subjected to experiments. The proposed method resulted in a mean precision score (mP@α) of 95.27%, 94.20%, 96.19%, and 96.05 forGT, LFW, Pointing ‘04, and our datasets, respectively. Also, the F-score was calculated that are, 96.78%, 95.15%, 97.08%, and 96.96%forGT, LFW, Pointing ‘04, and our datasets, respectively. The results obtained by the proposed method are comparable to the existing methods.

A potential damage mechanism of rubberized cement under freeze-thaw cycle

Abstract The recycling of scrap tires has attracted attention under the increasingly severe environmental pressures. Rubberized cement, a hardened cement paste with part of the aggregate replaced by rubber particles, shows non-brittle damage differing from the normal concrete. Therefore, there have been mounting interests in the durability of rubberized cement, especially the property against the freeze-thaw cycles. The changed behavior of rubberized cement may be attributed to the effect of rubber particles packing of cement mortar. However, very little progress has been made in exploring the failure mechanisms due to the complex interactions among the material components. The objective of this study is to investigate the damage mechanism of treated cement mortar with rubber particles in terms of freeze-thaw procedure. The cement mortar specimens were divided into two main components: cement paste and rubber particle, which are represented by two parameters: Relative Skeleton Strength (RSS) & Compressive Ratio (CR) respectively. The analysis is based on the Canonical correlation method and Spearman correlation method. The statistical analysis reveals that CR has a high correlation with the residual strength of the specimens after the freeze-thaw cycle.

ДІАГНОСТИКА ЕФЕКТИВНОСТІ ВИКОРИСТАННЯ ВИРОБНИЧИХ ФАКТОРІВ У БУДІВНИЦТВІ ЗАСОБАМИ КАНОНІЧНОГО АНАЛІЗУ

У статті обґрунтовано набір виробничих факторів, використання яких забезпечує основні результати будівельної діяльності. Доведено необхідність інтегрального оцінювання сукупного впливу факторів і обчислення узагальнюючого результативного показника методом канонічних кореляцій. Запропоновано методику якісного оцінювання ефективності будівельної діяльності на основі результатів канонічного аналізу у поєднанні з функціями бажаності Харрінгтона, яку застосовано для аналізу підприємств будівництва за 2017 р. в регіональному розрізі