Correlation Coefficient Analysis Research Articles

Flow boiling heat transfer of R454B in a 24-port microchannel tube

R454B is a relatively low Global Warming Potential refrigerant, and it has emerged as a promising substitute for traditional refrigerants. Understanding the heat transfer and fluid dynamics characteristics of R454B becomes important for applying it. An experimental setup was built for measuring heat transfer coefficient (HTC) and pressure gradient (dP/dz) in a 24-port microchannel tube. The test condition covers mass fluxes of 100–250 kg-m-2s−1, heat fluxes of 2–8 kW-m−2, and saturation temperatures of 10–30 °C. The mass flux had a significant impact on the HTC, particularly at higher vapor quality. Additionally, the heat flux also played a crucial role in determining the HTC, with a stronger influence observed at lower vapor quality. The saturation condition had a relatively minor effect on HTC, showing a positive impact at low vapor quality but a negative impact at moderate and high vapor quality. The dP/dz tended to increase with vapor quality. Both the mass flux and saturation condition exhibited strong effects on dP/dz. However, the heat flux had a negligible impact on the dP/dz. The study also compared the performance of R454B with R32, R1234yf, and three R32/R1234yf mixtures (85/15, 50/50, and 15/85 by mass). The results showed that R454B had a HTC close to R1234yf and the 85/15 mixture. However, it had the lowest dP/dz compared among the compared fluids. The results were compared to existing correlations and those with less error were recommended. This study pioneered the examination of R454B flow boiling in microchannel tubes, and employed Pearson correlation coefficient analysis which presents a first-of-its-kind quantitative analysis of the impact of operational conditions on HTC and dP/dz, marking a significant advancement in thermal systems optimization.

Deep learning-based correlation analysis for probabilistic power flow considering renewable energy and energy storage

Developing photovoltaic (PV) and wind power is one of the most efficient approaches to reduce carbon emissions. Accumulating the PV and wind energy resources at different geographical locations can minimize total power output variance as injected into the power systems. To some extent, a low degree of the variance amplitude of the renewable resources can reduce the requirement of in-depth regulation and dispatch for the fossil fuel-based thermal power plants. Such an issue can alternatively reduce carbon emissions. Thus, the correlation problem by minimizing the variance of total PV and wind power plays a vital role in power system planning and operation. However, the synergistic effect of power output correlation is mainly considered on the generation side, and it is often neglected for the correlation relationship between the power grid components. To address this problem, this paper proposes a correlation coefficient analysis method for the power grid, which can quantify the relationship between energy storage and the probabilistic power flow (PPF) of the grid. Subsequently, to accelerate the mapping efficiency of power correlation coefficients, a novel deep neural network (DNN) optimized by multi-task learning and attention mechanism (MA-DNN) is developed to predict power flow fluctuations. Finally, the simulation results show that in IEEE 9-bus and IEEE14-bus systems, the strong correlation grouping percentage between the power correlation coefficients and power flow fluctuations reached 92% and 51%, respectively. The percentages of groups indicating weak correlation are 4% and 38%. In the modified IEEE 23-bus system, the computational accuracy of MA-DNN is improved by 37.35% compared to the PPF based on Latin hypercube sampling. Additionally, the MA-DNN regression prediction model exhibits a substantial improvement in assessing power flow fluctuations in the power grid, achieving a speed enhancement of 758.85 times compared to the conventional probability power flow algorithms. These findings provide the rapid selection of the grid access point with the minimum power flow fluctuations.

Enterprise Risk Management Practices and Financial Performance of Apparel Industry in Sri Lanka

The apparel industry plays an important role in the Sri Lankan economy. However, based on the previous literature, apparel factories continuously face many internal and external risks and business recessions that affect their performance. Therefore, the main objective of this study is to identify the impact between enterprises' risk management practices and firm’s financial performance.To achieve the said objective, researchers carried out a questionnaire-based survey of 167 managers who were involved in enterprise risk management in the apparel industry in Sri Lanka, applying a simple random sampling method. This study is quantitative research that adopts ontological and positivist research philosophy. The Statistical analysis has been done through correlation coefficient analysis with the SPSS software.Results found that small apparel factories' risk management systems turned out to be relatively weak and informal. Further, firm size and management attitude toward risk have been shown to significantly impact enterprises’ risk management practices and company financial performance. The findings confirmed a strong positive correlation between risk management practices and financial performance in the Sri Lankan apparel sector.

Development of a deep-learning algorithm for age estimation on CT images of the vertebral column

PurposeThe accurate age estimation of cadavers is essential for their identification. However, conventional methods fail to yield adequate age estimation especially in elderly cadavers. We developed a deep learning algorithm for age estimation on CT images of the vertebral column and checked its accuracy. MethodFor the development of our deep learning algorithm, we included 1,120 CT data of the vertebral column of 140 patients for each of 8 age decades. The deep learning model of regression analysis based on Visual Geometry Group-16 (VGG16) was improved in its estimation accuracy by bagging. To verify its accuracy, we applied our deep learning algorithm to estimate the age of 219 cadavers who had undergone postmortem CT (PMCT). The mean difference and the mean absolute error (MAE), the standard error of the estimate (SEE) between the known- and the estimated age, were calculated. Correlation analysis using the intraclass correlation coefficient (ICC) and Bland-Altman analysis were performed to assess differences between the known- and the estimated age. ResultsFor the 219 cadavers, the mean difference between the known- and the estimated age was 0.30 years; it was 4.36 years for the MAE, and 5.48 years for the SEE. The ICC (2,1) was 0.96 (95 % confidence interval: 0.95–0.97, p < 0.001). Bland-Altman analysis showed that there were no proportional or fixed errors (p = 0.08 and 0.41). ConclusionsOur deep learning algorithm for estimating the age of 219 cadavers on CT images of the vertebral column was more accurate than conventional methods and highly useful.

Preferences and Constraints: A Study on Urban Outdoor Sportive Recreation Areas

It is increasingly important to identify the determinants and barriers to the use of urban parks. To this aim; the sample group in the study, which was carried out to determine the participation preferences and constraints of individuals using open space urban recreation areas, consists of 629 people using 11 urban open recreation areas in Turkey’s Ankara province. In addition to the demographic questionnaire, “Preference Factors of Recreation Areas” (PFRA) and “Sportive Recreation Barriers Scale” (SRBS) scales were used to collect the data. Frequency, arithmetic mean and standard deviation were used to analyze the data. Independent sample t test and one-way analysis of variance ANOVA test were applied to determine the difference since homogeneity and normal distribution conditions were fulfilled. Correlation coefficients were given by Pearson product-moment correlation coefficient and regression analysis was used. The findings obtained can be stated that individuals who use open space recreation areas in Ankara province have a high preference for recreation area participation and perceive sportive recreation barriers at average values. It was determined that the variables such as gender, education level, marital status and reasons for going to recreational areas significantly differentiated recreation area preference factors and sportive recreation barriers. It was found that there was a statistically significant relationship between PFRA and SRBS, and it was also found to be a factor in explaining the barriers to sportive recreation. Within the scope of the findings obtained, the findings were discussed with the support of the literature in terms of evaluating the preference factors of open space urban recreation area users for using parks and the barriers that they may encounter.

Comparative studies of four cumin landraces grown in Egypt

One of the significant aromatic plants applied in food and pharma is cumin. Despite its massive trading in Egypt, there are no comprehensive reports on cumin landraces profile screening. This study aimed to investigate the variation in seeds’ physical and biochemical profiles and genetic diversity as well as assess the efficiency of seeds’ germination under salinity stress. Consequently, during the 2020/2021 growing season, four common cumin seed landraces were gathered from various agro-climatic regions: El Gharbia, El Menia, Assiut, and Qena. Results showed a significant variation in physical profile among the four seeds of landraces. In addition, Assiut had the highest percentage of essential oil at 8.04%, whilst Qena had the largest amount of cumin aldehyde, the primary essential oil component, at 25.19%. Lauric acid was found to be the predominant fatty acid (54.78 to 62.73%). According to ISSR amplification, El Menia presented a negative unique band, whereas other landraces offered a positive band. Additionally, the cumin genotypes were separated into two clusters by the dendrogram, with El Gharbia being located in an entirely separate cluster. There were two sub-clusters within the other cluster: El Menia in one and Assiut and Qena in the other. Moreover, the germination sensitivity to the diverse salinity concentrations (control, 4, 8, 12, and 16 dS/m) findings showed that landraces exhibited varying responses to increased salinity when El Gharbia and El Menia showed a moderate response at four dS/m. Whilst, Qena landraces showed supreme values among other landraces under 12 and 16 dS/m. The majority of the examined features had strong positive associations over a range of salinity levels, according to phenotypic correlation coefficient analysis. To accomplish the aims of sustainable agriculture in Egypt, it would be imperative that the potential breeding program for cumin landraces consider this screening study.

Impact of body image and perceived stigmatization on the psychological wellbeing of obese women in Kumasi metropolis, Ghana.

Obesity is found to have a significant impact on body image perception and overall well-being. This study examines the impact of body image and perceived stigmatization on the psychological wellbeing of obese women in Kumasi metropolis, Ghana. A sample of 231 obese women was selected from health shops and some fitness centers using snowballing technique (purposive, snowballing technique and convenience). The study employed the descriptive survey design and made use of both descriptive and inferential data analysis approaches. The body shape questionnaire BSQ-34, the inventory of the Stigmatization Situation (SSI) and finally, the psychological well-being tools were used. Also, frequency distributions mean, and standard deviation, Pearson correlation coefficient and simple linear regression analysis were employed using SPSS version 23. Our findings indicated that obese women in the Kumasi metropolis were significantly satisfied with their body image. This is a true reflection of their higher self-esteem and standard of living. The body image and perceived stigmatization on the psychological wellbeing of the obese do have some counselling implications. Counselors, nutritionists, and clinical psychologists address specific schemes such as binge eating, dieting, and exercising to build the self-esteem of obese women.

Correlation and Path Analysis Studies in Mungbean [Vigna radiata (L.) Wilczek] under Arid Environment of Western Rajasthan

Background: Mungbean is an important grain legume crop. It contains a high amount of protein, carbohydrates, vitamins and minerals. The productivity of this crop is still low, hence efforts should be made to improve the yield of mungbean by keeping knowledge about association between seed yield and its components. Thus, the present investigation was aimed to determine the correlation and path coefficient analysis for seed yield and its attributing traits in mungbean. Methods: Seventy-nine diverse genotypes of mungbean were evaluated during Kharif 2017-18 for eleven quantitative traits in randomized block design with three replications at the Experimental farm, Department of Genetics and Plant Breeding, College of Agriculture, Swami Keshwanand Rajasthan Agricultural University, Bikaner, Rajasthan. Result: Significant genotypic differences were observed for all the traits studied indicating a considerable amount of variation among genotypes for all the characters. The seed yield per plant exhibited highly significant and positive correlation with number of pods per plant, biological yield per plant, harvest index, number of seeds per pod and pod length. The characteristics such as biological yield per plant, harvest index, number of pods per plant, pod length, number of seeds per pod, plant height, 100-seed weight and days to 50 per cent flowering had high positive direct effect on seed yield per plant. Therefore, selection based on the traits viz., number of pods per plant, biological yield per plant, harvest index, number of seeds per pod, 100-seed weight and pod length could help in enhancing the seed yield per plant in mungbean.

Correlation and path coefficient analyses for some yield-related traits in apple (Malus domestica Borkh) under mid-hill conditions of Himachal Pradesh, India

Correlation and path coefficient analyses for some yield-related traits in apple (Malus domestica Borkh) under mid-hill conditions of Himachal Pradesh, India

Suicidal Tendency and Impulsivity and Integrative Self-knowledge Among the Adult Population

Background: According to the World Health Organization, almost half of violent deaths globally are due to suicide. Development in effective prevention of suicide requires a better understanding of the potential processes underlying suicidal ideation and behavior. Objectives: The present study aimed to investigate the relationship between impulsivity with integrative self-knowledge and suicidal ideation in the adult population of Zahedan, Iran. Materials and Methods: The present descriptive-correlational study was conducted on 422 adults aged 20 years and older. The Beck scale for suicidal ideation, Barrat impulsiveness, and integrative self-knowledge scales were used to collect data. The data were analyzed using the Pearson correlation coefficient and regression analysis. Results: The results showed that impulsivity had a direct and significant relationship with a suicidal tendency. According to the results of stepwise regression analysis, the impulsivity variable explained 0.03% of the suicidal ideation variance, and self-knowledge could explain 0.11% of the suicidal tendency variance. Conclusions: In general, the obtained findings are consistent with the theory that impulsivity as a risk factor and cohesive self-awareness as a protective factor are associated with suicidal ideation and can be used as a step forward in finding useful solutions to prevent suicide. It is suggested that the results be evaluated prospectively in larger samples with a higher risk of suicide.

PENGARUH KUALITAS PELAYANAN DAN KUALITAS PRODUK TERHADAP KEPUASAN KONSUMEN PADA PT. AIRMAS PERKASA

The quality of products on consumer satisfaction at PT. Airmas Perkasa is good both partially and simultaneously. The method used is quantitative. The population consists of consumers who purchase IT &amp; Electronics products, with a sample collection technique using the Slovin formula, resulting in a sample of 98 respondents. Data analysis uses validity tests, reliability tests, classical assumption tests, regression analysis, correlation coefficient analysis, determination coefficient analysis, and hypothesis testing. The results of this study show that service quality partially influences positively and significantly on consumer satisfaction with a determination coefficient value of 80.6%, as evidenced by the hypothesis test results where the t-value &gt; t-table (19.961 &gt; 1.985). Product quality partially influences positively and significantly on consumer satisfaction with a determination coefficient value of 83.9%, as evidenced by the hypothesis test results where the t-value &gt; t-table (22.361 &gt; 1.985). Service quality and product quality simultaneously have a positive and significant influence on consumer satisfaction with the regression equation Y = 4.289 + 0.263X1 + 0.494X2. The determination coefficient value is 85.9%, as evidenced by the hypothesis test results where the F-value &gt; F-table (289.216 &gt; 3.091). Therefore, H0 is rejected, and H3 is accepted. This means that service quality and product quality have a positive and significant simultaneous influence on consumer satisfaction.

THE INFLUENCE OF MOTIVATION ON EMPLOYEE PERFORMANCE THROUGH COMPENSATION AS MEDIATION

This research investigates the relationship between employee motivation and performance at PT Karunia Gemilang, using an associative quantitative approach. The total sample used was 65 employees, representing all members of the company's population. Data analysis includes validity, reliability, simple linear regression, correlation coefficient analysis, and coefficient of determination. The results show that there is a strong and significant relationship between motivation and employee performance. The correlation coefficient of 0.768 indicates that motivation has a substantial influence on employee performance. Furthermore, the coefficient of determination of 59.0% indicates that most of the variability in employee performance can be explained by variability in their motivation. These findings emphasize the importance of effective motivation strategies in human resource management to optimize employee performance. This study highlights the important role of motivation in achieving organizational goals and increasing employee work effectiveness.

Perancangan Antarmuka Aplikasi Mobile Perguruan Tinggi Menggunakan Kansei Engineering (Studi Kasus: STIS Nahdatul Ulama Cianjur)

Mobile Apps program-based has given a major influence towards the education sector, specifically in general information about college, especially in stakeholder needs. On the other hand, it also assists in reading the latest events and news, the notification of class schedules, also the information of grades and attendances. The focus of this research is to analyze user preferences including increasing user satisfaction, user retention and design preferences for the interface of Sekolah Tinggi Ilmu Syariah Nahdatul Ulama College mobile app using the Kansei Engineering Type 1 method. The study used Kansei engineering method was conducted to analyze various emotional factors relating to the interface of users by comparing five specimens of college’s mobile apps. A total of twenty kansei words were found from thirty Kansei words based on the selection of UI/UX experts. The data obtained is then analyzed using multivariate statistical methods, such as Cronbach's Alpha (CA), Coefficient Correlation Analysis (CCA), and Factor Analysis (FA). The result is four Kansei words that are influential and have the greatest value, namely Dynamic, Impressive, Professional, and Formal. One selected Kansei word produces recommendations for the appearance of the mobile application interface Sekolah Tinggi Ilmu Syariah Nahdatul Ulama The analysis was conducted on all participants with a focus on the "Formal" emotion concept.

Future anxiety among media professionals and its relationship to utilizing artificial intelligence techniques: The case of Egypt, France, and UAE

This article aims to study professional future anxiety differences among media professionals and its relationship to utilizing artificial intelligence (AI) techniques in media institutions in Egypt, France, and United Arab Emirates (UAE); and to know the effect of the intensity of employing AI techniques in various media institutions on the professional future anxiety of the sample. A convenience sample was drawn from the three countries, with a total of 300 media professionals. It included 100 participants from each country, to whom the questionnaire and the professional future anxiety scale were applied. The methodology regarding data collection is quantitative research. Descriptive analysis was used to extract the results. Pearson correlation coefficient, ANOVA, and simple linear regression analysis to test the research hypotheses. The study revealed that there is a statistically significant direct correlation between the employment of AI techniques in media institutions and professional future anxiety among media professionals in Egypt, France, and UAE. It was also evidenced that there are differences in the degree to which media institutions employ AI technologies in favor of France, while no differences were found in the level of professional future anxiety among media professionals based on the variable of the country. The respondents’ degree of professional future anxiety was moderate. The results also confirmed that media institutions’ extensive employment of AI techniques contributes to effecting professional future anxiety among media professionals participating in the study. The most prominent technologies and applications employed by media institutions and were used by the respondents were techniques for verifying the accuracy of sources, information, and content, and techniques for increasing the efficiency of news coverage and processing, ChatGPT application.

Comparison of Spot Vision Screener and Tabletop Autorefractometer with Retinoscopy in the Pediatric Population.

Determining the accuracy of cycloplegic refractive error measurements made with the Spot Vision Screener (SVS, Welch Allyn Inc, Skaneateles Falls, NY, USA) is important for refractive assessment of uncooperative patients during optometric examinations. This study compared cycloplegic refractive errors measured by SVS and tabletop autorefractometer to cycloplegic retinoscopy in children. Eighty-eight eyes of 44 subjects were examined in the study. Refractive error measurements were obtained under cycloplegia using retinoscopy, SVS, and Nidek ARK-530 tabletop autorefractometer (ARK-530, Nidek, Japan). Spherical and cylindrical values, spherical equivalents (SE), and Jackson cross-cylinder values at axes of 0° (J0) and 45° (J45) were recorded. Correlations between methods were analyzed using intraclass correlation coefficient (ICC) and Bland-Altman analysis. The mean age was 7 years (range: 6 months-17 years). Sixteen (36%) of the subjects were female and 28 (64%) were male. For SE there was excellent agreement between retinoscopy and SVS (ICC: 0.924) and between retinoscopy and tabletop autorefractometer (ICC: 0.995). While there was a moderate correlation between retinoscopy and SVS for cylindrical values (ICC: 0.686), excellent correlation was detected between retinoscopy and autorefractometer (ICC: 0.966). J0 and J45 crosscylinder power values were not correlated between retinoscopy and SVS (ICC: 0.472) or retinoscopy and tabletop autorefractometer (ICC: 0.442). Retinoscopy was correlated with both SVS and tabletop autorefractometer for all parameters within ±1.96 standard deviations in Bland-Altman analysis. Cycloplegic retinoscopy is the gold standard for refractive error measurement in the pediatric population. However, it requires time and experienced professionals. This study revealed moderate to good agreement between SVS and retinoscopy, with better agreement in spherical errors than cylindrical errors. Although the SVS is intended for screening programs, it may also be useful in the pediatric eye office to estimate spherical refractive error in uncooperative patients.

Factors affecting success and failure in higher education mathematics: Students' and teachers’ perspectives

BackgroundStudents from Bangladesh pursuing STEM education often encounter obstacles when tackling diverse mathematical problems within various educational settings. Frequently, they find themselves lacking the essential prerequisite knowledge and strong foundational skills necessary to engage with the teaching and learning resources utilized at the undergraduate level, resulting in a significant number of students needing to seek readmission annually. ObjectiveThe objective of this study is to explore the determinants of academic achievement among university undergraduates majoring in mathematics in Bangladesh. Employing a mixed-method research approach, the study combines quantitative and qualitative data analysis to examine the viewpoints of both students and educators concerning these factors. The authors primarily emphasize classifying the factors that impact the efficacy of mathematics pedagogical methods. MethodologyThe study is structured into three phases: i. An initial exploratory qualitative survey. ii. A quantitative triangulation survey. iii. Followed by explanatory semi-structured interviews. FindingsTo begin, the initial qualitative survey identified significant factors that contribute to students' achievements and setbacks in mathematics. Subsequently, the quantitative analysis verified both similarities and distinctions in the perspectives of students and educators. Furthermore, the correlation coefficient analysis revealed that male students frequently exhibit inconsistency and a lack of enthusiasm for studying, resulting in subpar performance. Conversely, female students frequently cited challenges like the difficulty of connecting mathematical theories to real-world applications, heavy course loads, and limited resources as reasons for their academic difficulties. Lastly, insights from interviews with students highlighted their acknowledgment of inadequate study practices, excessive reliance on memorization, suboptimal teaching methods, low motivation, and external distractions as key factors leading to their struggles. They also recognized the importance of consistent practice, a solid comprehension of concepts, regular study routines, and effective learning strategies for successful mathematics education. In contrast, educators emphasized the significance of students having clear concepts, natural aptitude, motivation, and a sense of curiosity as pivotal elements for successful learning in mathematics. ConclusionThis conclusion suggests a new beginning in the realm of local mathematics pedagogy, achieved by scrutinizing teacher-student feedback about the factors influencing success and failure, considering the diverse individual and contextual variables at play. To foster mutual trust and understanding between students and teachers, it may be beneficial to engage in open discussions and interactions.

Multimodal machine learning for predicting heat transfer characteristics in micro-pin fin heat sinks

As three-dimensional integrated circuit (3D-IC) chip technology advances, thermal management has become increasingly important because of increasing heat flux from thermal stacking. Micro-pin fin-embedded cooling has emerged as a promising solution for 3D-ICs, offering better thermal and hydraulic performance than conventional microchannel heat sinks. It is also easy to integrate into existing 3D-IC structures, such as through-silicon vias between stacks. The utilization of two-phase flow in micro-pin fins further enhances temperature uniformity and improves the heat transfer coefficient by leveraging latent heat. Nevertheless, predicting thermal performance in micro-pin fin heat sinks under boiling conditions remains challenging owing to intricate geometric shapes and diverse operating conditions. The present lack of correlation or theoretical models poses a significant obstacle. To address this problem, our study employed a Multimodal machine-learning (ML) approach, combining image data capturing boiling patterns of two-phase flow and information about geometric shape and operating conditions, to predict heat transfer characteristics in micro-pin fin heat sinks. We utilized experimental data comprising 155 types of boiling heat transfer data with the dielectric fluid FC-72 in two micro-fin shapes directly etched on Si. Four ML algorithms (XGBoost, LightGBM, Multilayer perceptron (MLP), and Multimodal ML) were employed to predict thermal performance. The correlation coefficient analysis before learning revealed the influence of each type of measurement data on the heater surface temperature during two-phase flow. Prediction accuracy was measured using mean absolute percent error (MAPE), and the results were compared in terms of maximum and average temperature depending on the characteristics of each ML algorithm. Overall, the Multimodal approach demonstrated superior capability in predicting temperature distributions with spatial details, surpassing conventional decision-tree algorithms and MLP in performance. When trained with boiling images, the Multimodal ML model achieved remarkable precision, evidenced by a MAPE of 1.81% for the maximum temperature and 0.84% for the average temperature, highlighting its exceptional accuracy in mapping the heated surface temperature profile. By contrast, the traditional MLP model, which lacked training on boiling images, showed diminished accuracy, with a MAPE of 2.54% for the maximum temperature and 1.77% for the average temperature, indicating a comparative shortfall against the Multimodal model results.

Penggunaan Sistem Informasi Enterprise Resource Planning (ERP) dan Komunikasi Verbal terhadap Adaptive Performance

This research aims to find out how much influence the use of Enterprise Resource Planning (ERP) Information Systems and Verbal Communication has on Adaptive Performance at PT. Pratama Abadi Industri Sukabumi. The respondents in this study were 36 employees. This research method uses a quantitative method with an associative descriptive approach. This research carried out multiple correlation coefficient analysis, determination coefficient, multiple linear regression analysis, determination coefficient test and hypothesis testing partially (T test) and simultaneously using (F test). The results of this research show that there is a positive and significant influence between the use of Enterprise Resource Planning (ERP) Information Systems on Adaptive Performance. by producing Tcount greater than Ttable, namely (2.069&gt;2.034) with a significance of 0.046&gt;0.05. Verbal communication has a positive and significant effect on adaptive performance, this is proven by the results of Tcount being greater than Ttable, namely (2.063 &gt; 2.034) with a significance of 0.047 &gt; 0.05. The contribution in measuring the influence of the use of Enterprise Resource Planning (ERP) information systems and verbal communication on adaptive performance is 81.9%, while the remaining 18.1% is the influence of other factors outside this research. Keywords: Adaptive Performance, Enterprise Resource Planning (ERP), Verbal Communication

유아교사의 사회인지적 마음챙김이 창의성에 미치는 영향: 감정지능과 인지적 유연성의 순차적 매개효과 검증을 중심으로

The purpose of this study is to verify the sequential mediating effects of emotional intelligence and cognitive flexibility on the relationship between early childhood teachers' socio- cognitive mindfulness and creativity to examine individual internal factors that affect the creativity of early childhood teachers. For the purpose of this study, a survey was conducted targeting 225 homeroom teachers working in daycare centers and kindergartens located across the country. For the collected data, the frequency, percentage, mean, standard deviation were calculated and the relationships among the major variables were examined through a Pearson's moment correlation coefficient analysis. The main findings are as follows. First, the level of socio-cognitive mindfulness, emotional intelligence, cognitive flexibility and creativity of the participants in the study were all above usual. Second, it was found that emotional intelligence and cognitive flexibility were sequential partial mediating effects on the individual impacts of socio-cognitive mindfulness on creativity. These results recall the importance of early childhood teachers' creativity and provide basic data on how to improve early childhood teachers' creativity, which was found to be insufficient. In addition, in research on socio-cognitive mindfulness, emotional intelligence, and cognitive flexibility, which are factors that affect the creativity of early childhood teachers, is of great academic significance in that this study provides basic data on antecedent factors that help early childhood teachers address various situations or solve a range of problems.

Permissive Parenting, Self Regulation and Risk-Taking Behavior among Adolescents

The purpose of this study was to find out the relationship among permissive parenting, self-regulation and risk-taking behaviour among adolescents. Parents displaying a permissive parenting style often let their adolescents choose what to do. Due to the lack of boundaries and rules set under permissive parenting, adolescents may view their parents as more of a friend or an equal rather than a person of authority and this leads to poor self-regulation abilities among adolescents. A stratified random sampling technique was used in this study. 180 College students from the public and private colleges of Toba Tek Singh between the age range 12-18 were included in the study. PAQ developed by Buri (1991), ASRI developed by K.L (2007) Moilanen and RTSHIA by Vrouva (2010) were used. The Pearson correlation coefficient and regression analysis were used to examine correlation and the predictive relationship among the variables under investigation. The results of this study showed that there is a significant correlation between permissive parenting and self-regulation among adolescents. Permissive parenting strongly predicts self-regulation among adolescents.