Correlation Technique Research Articles

Mechanical Behaviour of 7075-T6 Aluminium Alloy: Integrating Digital Image Correlation and Finite Element Analysis for Uniaxial and Biaxial Load Scenarios

The objective of this study is to investigate the mechanical properties of 7075-T6 Aluminium (Al) alloy under both uniaxial and biaxial loads. The study will be conducted using a combination of experimental and numerical methods. The experimental method used is the digital image correlation (DIC) technique, which was utilized to capture the deformation and strain fields of the material specimen under tensile test. A tensile machine was employed to apply uniaxial and biaxial loads on the sample. The strain and deformation distribution of the results was generated on the DIC and correlated software. The numerical method involved the use of a commercial finite element software to create a finite element model and simulate the mechanical behaviour of the material under the same loading conditions. The results obtained from the experimental and numerical methods were compared to validate the accuracy of the numerical model. The outcomes demonstrated that under uniaxial loading, localized necking and fracture were observed, while biaxial loading resulted in shear deformation and fracture. This research contributes to the development of more accurate models for predicting the mechanical behaviour of the model samples under different loading conditions.

The Role of Organizational Culture in Employee Retention in Kosovar Businesses

This research aimed to examine the impact of organizational culture on employee retention, providing insights to enhance long-term engagement and satisfaction. A mixed-methods approach was used, beginning with a comprehensive literature review of organizational culture and employee retention. Surveys were conducted with a representative sample of employees across different sectors in Kosovo. The data were analyzed using regression and correlation techniques to identify quantitative relationships between organizational culture and retention. The findings reveal that organizational culture plays a significant role in employee retention. Specifically, cultures focused on employee well-being, career development, and transparency are positively associated with higher retention rates. Employees are more likely to stay with organizations that align with their values, offer support, and create a transparent working environment. Conversely, toxic cultures marked by negativity and poor leadership are linked to higher turnover. The study underscores the importance of fostering a positive, inclusive culture that prioritizes employee growth. Kosovar businesses should invest in employee development, training, and continuous feedback to build a productive environment that supports retention.

LEADERSHIP PRACTICES OF SCHOOL HEADS AND WORK TASK MOTIVATION AS PREDICTORS OF TEACHERS’ BEHAVIOR

This study determined the significant influence of school head leadership practices and work task motivation as predictors of teachers’ behaviour. The quantitative approach using the correlational technique and analysis was utilized in this study with a sample of 325 teachers from the elementary schools of Caraga District, Schools Division of the City of Davao Oriental. Sets of adapted survey questionnaires were used to obtain data from the respondents subjected to content validity and reliability analysis. The data were analyzed using the Mean, Pearson-r, and Multiple Regression Analysis. The results reveal that the leadership practices were rated very high, and work task motivation was also rated as high. At the same time, teacher behaviour was rated high. Moreover, a significant relationship existed between these variables. A significant relationship between leadership practices and teacher behaviour was significant. A significant relationship between work task motivation and teacher behaviour was also significant. The extent of the influence of predictor variables on teacher behaviour was proven significant in the study.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0789/a.php" alt="Hit counter" /></p>

Investigation of scale effects of rock bridges based on Multi-Physical field monitoring

The presence of rock bridges is crucial for ensuring the stability of rock slopes. However, evaluating the mechanical properties of rock bridges solely based on the joint persistence coefficient (K) raises doubts due to potential variations in the scales of rock bridges within a rock mass with a constant K value. In this study, direct shear tests with different scales were carried out on sandstone specimens. Acoustic Emission (AE) and Digital Image Correlation (DIC) techniques were utilized to monitor the damage procession of the specimens. The evolution process of the specimen was divided into stages and three threshold points were determined based on AE parameters. As the scale decreased, the Joint Roughness Coefficient (JRC) increased, the tensile failure increased, and the shear failure decreased. As the normal stress increased, the JRC with the same scale decreased, the tensile failure decreased, and the shear failure increased. The change of fracture mechanism was the primary reason for the strength deterioration with decreasing scales. The decrease of the scale was not conducive to the failure prediction. By improving the rock bridge failure potential (RBP) index, the proposed RBPn index could appropriately characterize scale effects under different normal stresses.

Use of Blockchain Technology in the Fashion Industry: Analysis of How Blockchain Technology Can Be Used to Improve Transparency, Traceability, and Sustainability in the Fashion Supply Chain

Aim: The aim of this study was to investigate the use of blockchain technology in the fashion industry and to analyze its potential to improve transparency, traceability, and sustainability in the supply chain. Methodology: The study was based on a self-administered questionnaire, which was completed by 200 participants involved in the fashion industry. Descriptive statistics and correlation techniques were used to analyze the data and to test the main hypotheses of the study. Originality/Value: This study adds to the growing body of research on the use of blockchain technology in the supply chain and provides valuable insights into the potential benefits and challenges of implementing blockchain technology in the fashion industry. The study also highlights the role that blockchain can play in improving transparency, traceability, and sustainability in the supply chain. Findings: The results of the study suggest that the use of blockchain technology can lead to a significant increase in transparency in the fashion industry, as well as a significant improvement in traceability and sustainability. The results provide evidence of the potential of blockchain technology to improve the overall accountability and performance of the fashion industry, and highlight the need for further research and investment in this area.

Parenting styles as predictors to female students’ sexual promiscuity in tertiary institution in delta state

This study investigated the relationship between parenting styles and female students’ sexual promiscuity in tertiary institutions in Delta State. The study was led by two research questions and two hypotheses. The study used an ex-post facto research design with a correlational technique. The population comprised all female students of tertiary institutions in Delta Central Senatorial District with a total sample of 1,566 students. Questionnaire was used as instrument of data collection. The questionnaire was validated by experts’ judgement and factor analysis, with a sound psychometric property indicating that the instrument is valid and reliable. The data obtained were analysed with the aid of regression statistics at 0.05 level of significance. The result showed a significant relationship between parenting styles and sexual promiscuity and that the relationship can be moderated by socio-economic status of parents. The study recommended amongst others that Parents should improve on their relationship with their adolescents and choose the right parenting style that will help the adolescents to abstain from risky sexual behaviour.

Urban Heat Island and Environmental Degradation Analysis Utilizing a Remote Sensing Technique in Rapidly Urbanizing South Asian Cities

Rapid urbanization in South Asian cities has triggered significant changes in land use and land cover (LULC), degrading natural biophysical components and intensifying urban heat islands (UHIs). This study investigated the impact of LULC changes on land surface temperature (LST) and the role of biophysical indicators in enhancing urban resilience to thermal extremes. We used Landsat satellite imageries from 1993 to 2023, conducted a comprehensive analysis of LULC changes, and estimated LST variations at 6-year intervals in the Dhaka, Gazipur, and Narayanganj districts in Bangladesh. Afterward, we performed statistical analysis upon employing correlation, regression, and principal component analysis (PCA) techniques to summarize information. The results reveal that 339.13 km2 worth of urban expansion has occurred in last 30 years, with an average annual growth rate of 3.5%, accompanied by a substantial reduction in water bodies (−139.17 km2) and vegetation cover. Consequently, summer temperatures exceeded approximately 36.52 °C in dense urban areas. Also, the results highlighted the strong influence of built-up areas (BSI and SAVI) on LST, while vegetation (NDVI) and water indices (NDWI) exhibited a negative association. The findings emphasize the urgency of integrating green infrastructure and deploying sustainable urban planning policies to mitigate the potential adverse impacts of scattered urbanization in the face of climate change.

Temperature and rate dependent shear characterization and modeling of spread-tow woven Flax/PP composite laminates

This paper investigates the in-plane shear behavior of spread-tow woven structured flax fiber-reinforced polypropylene composites, focusing on temperature and displacement rate effects. For this aim, the study includes bias-extension experiments to characterize the shear behavior of the material. Several experiments were conducted at different displacement rates and temperature levels. The temperature levels were chosen to encompass the material's behavior during solid and molten-state thermoforming, given the melting and decomposition temperatures acquired from differential scanning calorimetry and thermogravimetric analysis tests, respectively. A new fixture was designed and manufactured to allow pre-heating of the oven and rapid placement of the samples, which in turn, prevents their degradation for the time duration required to reach a uniform temperature distribution in the oven. During the experiments, the 3D digital image correlation technique accurately measured local deformations and strains on the specimen's surface under varying conditions. Further, a finite element model is developed, incorporating a fiber reorientation algorithm with a hypo-elastic shear model to simulate the material's temperature and rate-dependent behavior. The finite element shear angle distributions, as well as the shear angle-force and shear angle-displacement curves, are compared with the Digital Image Correlation (DIC) data and load measurements for different test conditions, showing good agreement between the numerical and experimental approaches.

The Influence of Emotional Instability on Weight Fluctuations

This study examines the relationships between psychological factors, specifically mood fluctuations, short temper, and feelings of negativity, and their impact on weight gain or loss among individuals. The objective is to determine how these emotional states individually and collectively influence weight changes, focusing on understanding their predictive power. A quantitative, cross-sectional design was employed. The analysis involved correlation and multiple regression techniques to explore the relationships between the variables. Results revealed that moodiness has the strongest positive correlation with weight changes and is the most significant predictor, explaining a substantial portion of the variance. Short temper and feelings of negativity also contributed to body weight variations, though to a lesser extent. The model explained the variance in weight outcomes, highlighting the meaningful role of psychological factors in weight management. This study contributes to the growing body of research emphasizing the need to integrate mental health support in weight management programs and policy interventions, recognizing the critical role of mental well-being in influencing physical outcomes such as weight fluctuations. The findings have important implications for healthcare providers, policymakers, and wellness programs aiming to address health's psychological and physical aspects.

Activation of Ms 6.9 Milin Earthquake on Sedongpu Disaster Chain, China with Multi-Temporal Optical Images

In recent years, disaster chains caused by glacier movements have occurred frequently in the lower Yarlung Tsangpo River in southwest China. However, it is still unclear whether earthquakes significantly contribute to glacier movements and disaster chains. In addition, it is difficult to measure the high-frequency and large gradient displacement time series with optical remote sensing images due to cloud coverage. To this end, we take the Sedongpu disaster chain as an example, where the Milin earthquake, with an epicenter 11 km away, occurred on 18 November 2017. Firstly, to deal with the cloud coverage problem for single optical remote sensing analysis, we employed multiple platform optical images and conducted a cross-platform correlation technique to invert the two-dimensional displacement rate and the cumulative displacement time series of the Sedongpu glacier. To reveal the correlation between earthquakes and disaster chains, we divided the optical images into three classes according to the Milin earthquake event. Lastly, to increase the accuracy and reliability, we propose two strategies for displacement monitoring, that is, a four-quadrant block registration strategy and a multi-window fusion strategy. Results show that the RMSE reduction percentage of the proposed registration method reaches 80%, and the fusion method can retrieve the large magnitude displacements and complete displacement field. Secondly, the Milin earthquake accelerated the Sedongpu glacier movement, where the pre-seismic velocities were less than 0.5 m/day, the co-seismic velocities increased to 1 to 6 m/day, and the post-seismic velocities decreased to 0.5 to 3 m/day. Lastly, the earthquake had a triggering effect around 33 days on the Sedongpu disaster chain event on 21 December 2017. The failure pattern can be summarized as ice and rock collapse in the source area, large magnitude glacier displacement in the moraine area, and a large volume of sediment in the deposition area, causing a river blockage.

Examining Cycle Threshold values in Repeat SARS-CoV-2 Cases: A Retrospective Analysis in Ireland

Abstract Background Effective public health management during the COVID-19 pandemic requires accurate differentiation between re-infections and residual viral RNA detections in repeat positive cases. This study investigates cycle threshold (CT) trends in repeat SARS-CoV-2 cases to discern between persistent viral remnants and active infections. Collaboration between contact tracing and laboratories is essential for shaping robust public health strategies. Methods A retrospective analysis was conducted on 427 individuals with repeat positive PCR tests. Data was collected at a contact tracing centre from March to August 2021. Key variables including age, gender, and biomedical markers (test intervals, CT values) were examined. Regression and correlation techniques assessed CT trends and their implications. Results Younger individuals (<60 years) occasionally exhibited significantly lower CT values in subsequent tests, suggesting potential re-infections, while older adults generally displayed higher CT values indicative of residual RNA. These age-specific CT trends were statistically significant and instrumental in refining testing protocols and isolation guidelines. Further analysis is expected to strengthen these findings Conclusions Collaborative approaches between contact tracing and laboratories are vital in shaping robust public health strategies for distinguishing between types of repeat infections. Revision of health policies is imperative to prevent unnecessary isolation and optimise healthcare workforce allocation during ongoing transmission periods. Key messages • Decisive decision-making skills are crucial in managing repeat SARS-CoV-2 infections. • Revised health policies align testing and isolation practices with empirical CT data, enhancing public health efficacy.

Understanding the Impact of Social and Facilitating Factors on Drone Adoption in the Takaful Sector of Malaysia and Indonesia

The takaful industry, a sector that is guided by Shariah-compliant principles, is progressively investigating cutting-edge technologies to improve service delivery and operational efficiency. This study investigates the influence of social factors and facilitating conditions on the intention to adopt drone technology within the Takaful sector in Malaysia and Indonesia. A quantitative research design was employed, with data collected from 68 Takaful professionals. The results were analyzed using correlation and regression techniques. The findings revealed that social influence and facilitating conditions significantly impact behavior intention, while performance and effort expectancy were found to be less important. Additionally, the study integrates Maqasid Shariah principles, ensuring that the adoption of drone technology aligns with Islamic ethical considerations. The study also urges more investigation to investigate the generalisability of these results over many cultural and legal environments as well as the possible impact of developing technologies like artificial intelligence and blockchain on the sector.

The Relationship Between Peer Groups and the Learning Independence of Biology Education Students

Purpose of the study: This research aims to determine the relationship between peer groups and the learning independence of biology education students. Methodology: This type of research is quantitative with a correlation method. The population of this study was Biology Education Students, totaling 263 people with a sample size of 132 people. Sampling was carried out using Simple Random Sampling. The data collection techniques used are the learning independence scale and the peer group scale. The data analysis technique is descriptive statistical analysis and inferential statistical analysis with product moment correlation techniques. Main Findings: The research results based on descriptive statistical analysis show that independence in learning is in the low category with an average value of 88.56 and the peer group is in the medium category with an average value of 87. Meanwhile, the results of inferential statistical analysis show that rcount is greater than rtable or 0.27 ≥ 0.24, H0 is rejected and H1 is accepted, meaning that there is a relationship between the peer group and the learning independence of students. Where is the sig value. 2-tailed is 0.00 ≤ 0.05. Novelty/Originality of this study: This research contributes to explaining the social aspects of independent learning that are often overlooked in previous literature. While much research has explored internal factors that influence learning independence, the emphasis on the role of peer groups as external agents influencing students' motivation, mindset, and learning styles, is an innovative focus point. This enriches our insight into how social interaction with fellow students can have a significant influence on the level of learning independence of Biology Education students.

Servant Leadership of School Heads, Organizational Culture and Teamwork: A Causal Model on Teacher Engagement of Public Secondary School Teachers

This study aims to determine the best-fit structural model for teacher engagement of public secondary school teachers in Region XI, Philippines. It examines the interplay between exogenous variables: servant leadership of school heads, organizational culture, and teamwork on teacher engagement. It tries to understand how these factors influence each other and contribute to fostering a more engaging environment for teachers. The study utilized a descriptive correlational technique through structural equation modeling (SEM). Selected were 400 respondents using stratified random sampling. Findings show that servant leadership of school heads; organizational culture; and teamwork showed significant relationships with the endogenous variable, teacher engagement. Further, results showed that the best-fit model is the Generated Model 3 showing a direct causal relationship of the exogenous and endogenous variables. Furthermore, structure modifications revealed that servant leadership of school heads was grounded by the retained indicators: building community and empowering people which is highly reinforced by organizational culture, described by retained indicators- organizational management and organizational cohesion. Likewise, teamwork was strengthened by the retained indicators: communication and coordination. When the results of this study are given consideration, the goal of quality education in the Sustainable Development Goals that is quality education is positively achieved which resulted from highly engaged teachers.

Investigation on fatigue damage of buton rock asphalt mixtures using semi-circular bending (SCB) and digital image correlation (DIC) techniques

The fatigue performance evaluation indices of Buton rock asphalt (BRA) modified asphalt mixture struggles to accurately characterize damage evolution process under repeated loads of the traffic. This study employs digital image correlation (DIC) technology to assess the fatigue behavior of BRA modified asphalt mixture, quantify the correlation between macroscopic response and local deformation, and verify the accuracy of evaluation indices. By capturing strain and displacement fields, the fatigue damage evolution of BRA modified asphalt is analyzed. Based on fracture mechanics theory, BRA’ s improvement of fatigue performance is quantified. Results show that vertical displacement captured by DIC can divide the three stages of fatigue cracking. The global horizontal strain(GExx)and cumulative horizontal strain(CExx) proposed in this study better characterize the nonlinear fatigue damage evolution compared to horizontal strain(Exx). Adding BRA delays crack initiation, reduces propagation rate, and enhances fatigue performance. Strain field evolution was quantitatively analyzed, and horizontal strain density(DE) and global horizontal strain density(GDE) were proposed as fatigue damage indicators. At the same load level, these indicators in BRA modified asphalt mixture, both pre- and post-aging, exceeded those of neat asphalt mixture. These findings provide a novel and accurate approach for evaluating the fatigue damage behavior of BRA modified asphalt mixture, laying the foundation for future performance-based designs.

Experimental study on the compression and shear deformation evolution of coal pillar dam samples

To understand the mechanical properties and deformation failure patterns of coal pillar dams in gently inclined coal seam mine underground reservoirs, compression-shear coupling tests with variable angles were conducted on coal pillar dam samples under different saturation states. The digital image correlation (DIC) technique was utilized to obtain the deformation patterns of the displacement field throughout the compression-shear failure process of the samples. Numerical simulations were used to perform a comparative analysis and validation of the experimental results. The results indicated that the load-bearing capacity of the coal pillar dam samples decreased by 12.8–17.4% under water-saturated conditions. For every 5° increase in the inclination angle, the load-bearing capacity of the coal pillar dam samples decreased by an average of 3.53%. The normal stress and shear stress on the shear surface of the saturated samples were both lower than those of the natural samples, and both exhibited a linear variation with increasing inclination angle. The deformation evolution of the coal pillar dam samples under different test conditions exhibited similarity. The initial positive and negative displacement extremities in the horizontal direction were located at the lower right and upper left corners of the samples, respectively. Ultimately, the displacement field of the samples showed a pattern of smaller displacements at the top and larger displacements at the bottom, with negative values at the top and positive values at the bottom, distributed along the direction of the sample’s bedding. The saturated state and the increase in inclination both had a weakening effect on the load-bearing performance of the samples but had a relatively small impact on the differences in the displacement field deformation patterns. The research results can provide a reference for the study of the stability of coal pillar dams under similar conditions.

Optimized variational mode decomposition for improved bearing fault diagnosis and performance evaluation

This research presents an enhanced methodology for diagnosing bearing faults using Variational Mode Decomposition (VMD) based on L-Kurtosis analysis. The proposed method focuses on selecting optimal parameters for VMD to extract the mode containing the most information related to the fault. The selection of these parameters is based on comparing the energy ratio of each mode and the absolute difference in L-Kurtosis between the Intrinsic Mode Function (IMF) with the highest energy and the original signal. The extracted mode is further refined using a specified kurtosis rate threshold to ensure the most relevant significant modes are captured. The proposed methodology was tested using real fault data from the CWRU, XJTU-SY, and a real-world wind turbine dataset related to electric motors and wind turbine systems. The results demonstrated high accuracy in fault detection compared to other methods such as the Gini Index, correlation, and traditional decomposition techniques like EMD. Furthermore, due to the simple computational nature of the improved VMD method, it is faster and more efficient compared to methods that rely on complex calculations or frequency band analysis, making it suitable for applications requiring real-time, reliable fault diagnosis

Damage behavior and toughening mechanism of SiCf/SiC-Ti3SiC2 composites: A combination of digital image correlation and acoustic emission

Matrix modification is an effective method to improve the mechanical properties of ceramic matrix composites, while the elucidation of corresponding damage mechanism is essential for the design and engineering application of composites. In this work, Ti3SiC2 particles were introduced into SiC matrix to fabricate Ti3SiC2 modified SiCf/SiC (SiCf/SiC-Ti3SiC2) composites by a hybrid technique of slurry suspension impregnation combined with polymer infiltration and pyrolysis. Compared with SiCf/SiC composites, the flexural strength and modulus of SiCf/SiC-Ti3SiC2 composites were increased by 17.8 % and 61.0 %, respectively. The three-point flexural damage behavior and failure mechanism of composites were systematically investigated and compared by the combination of digital image correlation and acoustic emission techniques. Based on the collaborative analysis of in-situ damage process, matrix micro-zone toughness and fracture morphology, the modification effect and toughening mechanism of Ti3SiC2 were revealed. The improved mechanical properties of SiCf/SiC-Ti3SiC2 composite could be ascribed to the more sufficient matrix cracking before composite failure and the increased matrix fracture energy by microcrack deflection. After matrix modification, the failure mechanism was dominated by the gradual propagation and growth of microcracks until the critical crack size, instead of the fast and unstable propagation of main crack.

Hubungan antara Self Efficacy dengan Flow Academic terhadap Mata Pelajaran Matematika Siswa Kelas XII SMA Adabiah 2 Kota Padang

This study aims to explore the relationship between self efficacy and academic flow in mathematics subjects among grade XII students of SMA Adabiah 2 Padang. The independent variable in this study is self efficacy, while the dependent variable is academic flow. The sampling technique used was simple random sampling, with a sample size of 135 grade XII students of SMA Adabiah 2 Padang. To test the validity and reliability, the Alpha Cronbach technique was used, with a self efficacy scale consisting of 15 items and a coefficient of 0.760, and an academic flow scale consisting of 17 items with a coefficient of 0.877. Data analysis was carried out using the parametric method using the Pearson product moment correlation technique, with the help of SPSS 27.0 software. The results of the analysis show a correlation coefficient of r = 0.536 and a p value of 0.000, which means the alternative hypothesis (H1) is accepted and the null hypothesis (H0) is rejected. The findings of this study indicate a positive relationship between self-efficacy and academic flow in mathematics subjects in grade XII students of SMA Adabiah 2 Padang.

Dividend Policy and Share Price Volatility of Listed Construction Firms at the Nairobi Securities Exchange, Kenya

The inherent volatility in all stock market scares low risk takers from the financial market and is capable of deterring investments. One of the factors that drives investors’ reactions to stock pricing is the dividend policy. This study examined the influence of dividend policy on the volatility of stock prices of construction firms listed at the Nairobi Securities Exchange for the period spanning five (5) years from 2019 to 2023. The study was dealt with on the following objectives; to examine the influence of dividend pay-out on share price volatility of listed construction firms at the NSE, Kenya, to determine the influence of dividend yield on share price volatility of listed construction firms at the NSE, Kenya. The study was guided by the: Dividend relevance theory, and dividend irrelevance theory. This study adopted a correlational research design while dealing with the research objectives. A census method was employed in data collection before analysis of the audited financial statements that was downloaded from the firm websites in arriving at detailed and well informed conclusions by employing Multiple regression, Correlation and ANOVA techniques using the Statistical Package for Social Sciences (SPSS) to establish the existence (or lack of it) of the relationship between the independent variables and the dependent variable of the study. The findings revealed that dividend policy influenced share price volatility by; dividend pay-out ratio (r=0.111, β=0.036, t=4.7240); and dividend yield (r= -0.018, β= -0.003, t= 2.7130). The study recommended that potential and existing investors should opt for listed firms in the construction sector with a high dividend payout ratio compared to the earnings generated by the firms; Investors to invest in firms with high dividend payouts. The study achieved its main objective. Keywords: Dividend Policy, Dividend Pay-out, Dividend Yield, Share Price Volatility