Search results for: correlation of random variables
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8974

Search results for: correlation of random variables

8854 Gray Level Image Encryption

Authors: Roza Afarin, Saeed Mozaffari

Abstract:

The aim of this paper is image encryption using Genetic Algorithm (GA). The proposed encryption method consists of two phases. In modification phase, pixels locations are altered to reduce correlation among adjacent pixels. Then, pixels values are changed in the diffusion phase to encrypt the input image. Both phases are performed by GA with binary chromosomes. For modification phase, these binary patterns are generated by Local Binary Pattern (LBP) operator while for diffusion phase binary chromosomes are obtained by Bit Plane Slicing (BPS). Initial population in GA includes rows and columns of the input image. Instead of subjective selection of parents from this initial population, a random generator with predefined key is utilized. It is necessary to decrypt the coded image and reconstruct the initial input image. Fitness function is defined as average of transition from 0 to 1 in LBP image and histogram uniformity in modification and diffusion phases, respectively. Randomness of the encrypted image is measured by entropy, correlation coefficients and histogram analysis. Experimental results show that the proposed method is fast enough and can be used effectively for image encryption.

Keywords: correlation coefficients, genetic algorithm, image encryption, image entropy

Procedia PDF Downloads 308
8853 Relationship between Monthly Shrimp Catch Rates and the Oceanography-Related Variables

Authors: Hussain M. Al-foudari, Weizhong Chen, James M. Bishop

Abstract:

Correlations between oceanographic variables and monthly catch rates of total shrimp and those of each of the major species (Penaeus semisulcatus, Metapenaeus affinis and Parapenaeopsis stylifera) showed significant differences for particular conditions. Catches of P. semisulcatus were basically positively correlated with temperature, i.e., the higher the temperature, the higher the catch rate, while those of M. affinis and P. stylifera were negatively correlated with temperature, i.e., high catch rates occurred in the low temperature waters. Thus, during the months January and April, P. semisulcatus preferred waters with high temperature, usually the offshore and southern areas, while M. affinis and P. stylifera preferred waters with low temperature, usually inshore and northern areas. The relationships between the catch rate of P. semisulcatus and salinity were not so clear. Results indicated that although salinity was one of the factors affecting the distribution of P. semisulcatus, it was not the principal factor, and impacts from other variables, such as temperature, might overshadow the correlation between the catch rates of P. semisulcatus and salinity. The relationship between shrimp catch rates and dissolved oxygen (DO) also showed mixed results. The catch rates of M. affinis increased with a decrease of surface DO in November 2013, but decreased with lower bottom DO in December. These results indicated that DO might be a factor affecting distributions of the shrimp; however; the true correlation between catch rate and DO might be easily overshadowed by other environmental variables. Catch rates of P. semisulcatus did not show any relationship with depth. P. semisulcatus is a migratory species and widely distributed in Kuwait's waters.During the shrimp season from July through December, P. semisulcatus occurs in almost all areas in Kuwait's waters irrespective of water depth. The catch rates of M. affinis and P. stylifera, however, showed clear relationships with depth. Both species had significantly higher catch rates in shallower waters, indicative of their restricted distribution.

Keywords: Kuwait, Penaeus semisulcatus, Metapenaeus affinis, Parapenaeopsis stylifera, Arabian gulf

Procedia PDF Downloads 472
8852 Pre-Analytical Laboratory Performance Evaluation Utilizing Quality Indicators between Private and Government-Owned Hospitals Affiliated to University of Santo Tomas

Authors: A. J. Francisco, K. C. Gallosa, R. J. Gasacao, J. R. Ros, B. J. Viado

Abstract:

The study focuses on the use of quality indicators (QI)s based on the standards made by the (IFCC), that could effectively identify and minimize errors occurring throughout the total testing process (TTP), in order to improve patient safety. The study was conducted through a survey questionnaire that was given to a random sample of 19 respondents (eight privately-owned and eleven government-owned hospitals), mainly CMTs, MTs, and Supervisors from UST-affiliated hospitals. The pre-analytical laboratory errors, which include misidentification errors, transcription errors, sample collection errors and sample handling and transportation errors, were considered as variables according to the IFCC WG-LEPS. Data gathered were analyzed using the Mann-Whitney U test, Percentile, Linear Regression, Percentage, and Frequency. The laboratory performance of both hospitals is High level. There is no significant difference between the laboratory performance between the two stated variables. Moreover, among the four QIs, sample handling and transportation errors contributed most to the difference between the two variables. Outcomes indicate satisfactory performance between both variables. However, in order to ensure high-quality and efficient laboratory operation, constant vigilance and improvements in pre-analytical QI are still needed. Expanding the coverage of the study, the inclusion of other phases, utilization of parametric tests are recommended.

Keywords: pre-analytical phase, quality indicators, laboratory performance, pre-analytical error

Procedia PDF Downloads 125
8851 Exploring the Relationships between Cyberbullying Perceptions and Facebook Attitudes of Turkish Students

Authors: Yavuz Erdoğan, Hidayet Çiftçi

Abstract:

Cyberbullying, a phenomenon among adolescents, is defined as actions that use information and communication technologies such as social media to support deliberate, repeated, and hostile behaviour by an individual or group. With the advancement in communication and information technology, cyberbullying has expanded its boundaries among students in schools. Thus, parents, psychologists, educators, and lawmakers must become aware of the potential risks of this phenomenon. In the light of these perspectives, this study aims to investigate the relationships between cyberbullying perception and Facebook attitudes of Turkish students. A survey method was used for the study and the data were collected by “Cyberbullying Perception Scale”, “Facebook Attitude Scale” and “Personal Information Form”. For this purpose, study has been conducted during 2014-2015 academic year, with a total of 748 students with 493 male (%65.9) and 255 female (%34.1) from randomly selected high schools. In the analysis of data Pearson correlation and multiple regression analysis, multivariate analysis of variance (MANOVA) and Scheffe post hoc test has been used. At the end of the study, the results displayed a negative correlation between Turkish students’ Facebook attitudes and cyberbullying perception (r=-.210; p<0.05). In order to identify the predictors of students’ cyberbullying perception, multiple regression analysis was used. As a result, significant relations were detected between cyberbullying perception and independent variables (F=5.102; p<0.05). Independent variables together explain 11.0% of the total variance in cyberbullying scores. The variables that significantly predict the students’ cyberbullying perception are Facebook attitudes (t=-5.875; p<0.05), and gender (t=3.035; p<0.05). In order to calculate the effects of independent variables on students’ Facebook attitudes and cyberbullying perception MANOVA was conducted. The results of the MANOVA indicate that the Facebook attitudes and cyberbullying perception were significantly differed according to students’ gender, age, educational attainment of the mother, educational attainment of the father, income of the family and daily usage of internet.

Keywords: facebook, cyberbullying, attitude, internet usage

Procedia PDF Downloads 390
8850 Generation of Symmetric Key Using Randomness of Hash Function

Authors: Sai Charan Kamana, Harsha Vardhan Nakkina, B.R. Chandavarkar

Abstract:

In a highly secure and robust key generation process, a key role is played by randomness and random numbers when current real-world cryptosystems are observed. Most of the present-day cryptographic protocols depend upon the Random Number Generators (RNG), Pseudo-Random Number Generator (PRNG). These protocols often use noisy channels such as Disk seek time, CPU temperature, Mouse pointer movement, Fan noise to obtain true random values. Despite being cost-effective, these noisy channels may need additional hardware devices to continuously communicate with them. On the other hand, Hash functions are Pseudo-Random (because of their requirements). So, they are a good replacement for these noisy channels and have low hardware requirements. This paper discusses, some of the key generation methodologies, and their drawbacks. This paper explains how hash functions can be used in key generation, how to combine Key Derivation Functions with hash functions.

Keywords: key derivation, hash based key derivation, password based key derivation, symmetric key derivation

Procedia PDF Downloads 140
8849 The Effect of Diet Intervention for Breast Cancer: A Meta-Analysis

Authors: Bok Yae Chung, Eun Hee Oh

Abstract:

Breast cancer patients require more nutritional interventions than others. However, a few studies have attempted to assess the overall nutritional status, to reduce body weight and BMI by improving diet, and to improve the prognosis of cancer for breast cancer patients. The purpose of this study was to evaluate the effect of diet intervention in the breast cancer patients through meta-analysis. For the study purpose, 16 studies were selected by using PubMed, ScienceDirect, ProQuest and CINAHL. Meta-analysis was performed using a random-effects model, and the effect size on outcome variables in breast cancer was calculated. The effect size for outcome variables of diet intervention was a large effect size. For heterogeneity, moderator analysis was performed using intervention type and intervention duration. All moderators did not significant difference. Diet intervention has significant positive effects on outcome variables in breast cancer. As a result, it is suggested that the timing of the intervention should be no more than six months, but a strategy for sustaining long-term intervention effects should be added if nutritional intervention is to be administered for breast cancer patients in the future.

Keywords: breast cancer, diet, mete-analysis, intervention

Procedia PDF Downloads 417
8848 Relationship Between In-Service Training and Employees’ Feeling of Psychological Ownership

Authors: Mahsa Kallhor Mohammadi, Hamideh Reshadatjoo

Abstract:

This study verified the relationship between in-service training and employees’ feeling of psychological ownership. This research applied a descriptive survey that investigated a correlation between variables. The target population was 140 employees of a Drilling Fluid and Waste Management Service Company, and the sample was 123 employees who were selected randomly and encouraged to complete an electronic questionnaire which was designed based on standard questionnaires for research variables covering 62 questions. The face validity of the questionnaire was supported by an experimental test, and its content validity was approved by the thesis supervisor and consulting advisor. For the descriptive statistics frequency tables and diagrams, measures of central tendency such as mode, median, and mean and measures of variability such as variance, standards deviation, and quartile deviation were used. In the inferential statistics section, the Pearson correlation coefficient was used to verify the relationship between the variables of the research. According to the results, all of the research hypotheses were supported. According to hypothesis 1, there was a positive and significant relationship between training policy-making and employees’ psychological ownership (r=0/408, α=0/05). According to hypothesis 2, there was a positive and significant relationship between training planning and employees’ psychological ownership (r=0/446, α=0/05). According to hypothesis 3, there was a positive and significant relationship between providing the training and employees’ psychological ownership (r=0/512, α=0/05). According to hypothesis 4, there was a positive and significant relationship between training performance management and employees’ psychological ownership (r=0/462, α=0/05). According to hypothesis 5, there was a positive and significant relationship between employees’ motivation and psychological ownership (r=0/694, α=0/05). Therefore, through systematic in-service training, which is in the same line with the strategic goals of an organization and is based on scientific needs analysis, design, implementation, and evaluation, it is possible to improve employees’ sense of psychological ownership toward an organization.

Keywords: in-service training, motivation, organizational behavior, psychological ownership

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8847 Some Accuracy Related Aspects in Two-Fluid Hydrodynamic Sub-Grid Modeling of Gas-Solid Riser Flows

Authors: Joseph Mouallem, Seyed Reza Amini Niaki, Norman Chavez-Cussy, Christian Costa Milioli, Fernando Eduardo Milioli

Abstract:

Sub-grid closures for filtered two-fluid models (fTFM) useful in large scale simulations (LSS) of riser flows can be derived from highly resolved simulations (HRS) with microscopic two-fluid modeling (mTFM). Accurate sub-grid closures require accurate mTFM formulations as well as accurate correlation of relevant filtered parameters to suitable independent variables. This article deals with both of those issues. The accuracy of mTFM is touched by assessing the impact of gas sub-grid turbulence over HRS filtered predictions. A gas turbulence alike effect is artificially inserted by means of a stochastic forcing procedure implemented in the physical space over the momentum conservation equation of the gas phase. The correlation issue is touched by introducing a three-filtered variable correlation analysis (three-marker analysis) performed under a variety of different macro-scale conditions typical or risers. While the more elaborated correlation procedure clearly improved accuracy, accounting for gas sub-grid turbulence had no significant impact over predictions.

Keywords: fluidization, gas-particle flow, two-fluid model, sub-grid models, filtered closures

Procedia PDF Downloads 103
8846 Estimation of Population Mean under Random Non-Response in Two-Phase Successive Sampling

Authors: M. Khalid, G. N. Singh

Abstract:

In this paper, we have considered the problem of estimation for population mean, on current (second) occasion in the presence of random non response in two-occasion successive sampling under two phase set-up. Modified exponential type estimators have been proposed, and their properties are studied under the assumptions that numbers of sampling units follow a distribution due to random non response situations. The performances of the proposed estimators are compared with linear combinations of two estimators, (a) sample mean estimator for fresh sample and (b) ratio estimator for matched sample under the complete response situations. Results are demonstrated through empirical studies which present the effectiveness of the proposed estimators. Suitable recommendations have been made to the survey practitioners.

Keywords: successive sampling, random non-response, auxiliary variable, bias, mean square error

Procedia PDF Downloads 502
8845 Joint Modeling of Longitudinal and Time-To-Event Data with Latent Variable

Authors: Xinyuan Y. Song, Kai Kang

Abstract:

Joint models for analyzing longitudinal and survival data are widely used to investigate the relationship between a failure time process and time-variant predictors. A common assumption in conventional joint models in the survival analysis literature is that all predictors are observable. However, this assumption may not always be supported because unobservable traits, namely, latent variables, which are indirectly observable and should be measured through multiple observed variables, are commonly encountered in the medical, behavioral, and financial research settings. In this study, a joint modeling approach to deal with this feature is proposed. The proposed model comprises three parts. The first part is a dynamic factor analysis model for characterizing latent variables through multiple observed indicators over time. The second part is a random coefficient trajectory model for describing the individual trajectories of latent variables. The third part is a proportional hazard model for examining the effects of time-invariant predictors and the longitudinal trajectories of time-variant latent risk factors on hazards of interest. A Bayesian approach coupled with a Markov chain Monte Carlo algorithm to perform statistical inference. An application of the proposed joint model to a study on the Alzheimer's disease neuroimaging Initiative is presented.

Keywords: Bayesian analysis, joint model, longitudinal data, time-to-event data

Procedia PDF Downloads 126
8844 Spatially Random Sampling for Retail Food Risk Factors Study

Authors: Guilan Huang

Abstract:

In 2013 and 2014, the U.S. Food and Drug Administration (FDA) collected data from selected fast food restaurants and full service restaurants for tracking changes in the occurrence of foodborne illness risk factors. This paper discussed how we customized spatial random sampling method by considering financial position and availability of FDA resources, and how we enriched restaurants data with location. Location information of restaurants provides opportunity for quantitatively determining random sampling within non-government units (e.g.: 240 kilometers around each data-collector). Spatial analysis also could optimize data-collectors’ work plans and resource allocation. Spatial analytic and processing platform helped us handling the spatial random sampling challenges. Our method fits in FDA’s ability to pinpoint features of foodservice establishments, and reduced both time and expense on data collection.

Keywords: geospatial technology, restaurant, retail food risk factor study, spatially random sampling

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8843 Effect of Pre-Aging and Aging Parameters on Mechanical Behavior of Be-Treated 7075 Aluminum Alloys: Experimental Correlation using Minitab Software

Authors: M. Tash, S. Alkahtani

Abstract:

The present study was undertaken to investigate the effect of pre-aging and aging parameters (time and temperature) on the mechanical properties of Al-Mg-Zn (7075) alloys. Ultimate tensile strength, 0.5% offset yield strength and % elongation measurements were carried out on specimens prepared from cast and heat treated 7075 alloys. Duplex aging treatments were carried out for the as solution treated (SHT) specimens (pre-aged at different time and temperature followed by high temperature aging). A statistical design of experiments (DOE) approach using fractional factorial design was applied to determine the influence of controlling variables of pre-aging and aging treatment parameters and any interactions between them on the mechanical properties of 7075 alloys. A mathematical models are developed to relate the alloy ultimate tensile strength, yield strength and % elongation with the different pre-aging and aging parameters i.e. Pre-aging Temperature (PA T0C), Pre-aging time (PA t h), Aging temperature (AT0C), Aging time (At h), to acquire an understanding of the effects of these variables and their interactions on the mechanical properties of be-treated 7075 alloys.

Keywords: aging heat Treatment, tensile properties, be-treated cast Al-Mg-Zn (7075) alloys, experimental correlation

Procedia PDF Downloads 257
8842 Establishment of the Regression Uncertainty of the Critical Heat Flux Power Correlation for an Advanced Fuel Bundle

Authors: L. Q. Yuan, J. Yang, A. Siddiqui

Abstract:

A new regression uncertainty analysis methodology was applied to determine the uncertainties of the critical heat flux (CHF) power correlation for an advanced 43-element bundle design, which was developed by Canadian Nuclear Laboratories (CNL) to achieve improved economics, resource utilization and energy sustainability. The new methodology is considered more appropriate than the traditional methodology in the assessment of the experimental uncertainty associated with regressions. The methodology was first assessed using both the Monte Carlo Method (MCM) and the Taylor Series Method (TSM) for a simple linear regression model, and then extended successfully to a non-linear CHF power regression model (CHF power as a function of inlet temperature, outlet pressure and mass flow rate). The regression uncertainty assessed by MCM agrees well with that by TSM. An equation to evaluate the CHF power regression uncertainty was developed and expressed as a function of independent variables that determine the CHF power.

Keywords: CHF experiment, CHF correlation, regression uncertainty, Monte Carlo Method, Taylor Series Method

Procedia PDF Downloads 397
8841 TRNG Based Key Generation for Certificateless Signcryption

Authors: S.Balaji, R.Sujatha, M. Ramakrishnan

Abstract:

Signcryption is a cryptographic primitive that fulfills both the functions of digital signature and public key encryption simultaneously in low cost when compared with the traditional signature-then-encryption approach. In this paper, we propose a novel mouse movement based key generation technique to generate secret keys which is secure against the outer and insider attacks. Tag Key Encapsulation Mechanism (KEM) process is implemented using True Random Number Generator (TRNG) method. This TRNG based key is used for data encryption in the Data Encapsulation Mechanism (DEM). We compare the statistical reports of the proposed system with the previous methods which implements TKEM based on pseudo random number generator

Keywords: pseudo random umber generator, signcryption, true random number generator, node deployment

Procedia PDF Downloads 322
8840 A Quantitative Analysis for the Correlation between Corporate Financial and Social Performance

Authors: Wafaa Salah, Mostafa A. Salama, Jane Doe

Abstract:

Recently, the corporate social performance (CSP) is not less important than the corporate financial performance (CFP). Debate still exists about the nature of the relationship between the CSP and CFP, whether it is a positive, negative or a neutral correlation. The objective of this study is to explore the relationship between corporate social responsibility (CSR) reports and CFP. The study uses the accounting-based and market-based quantitative measures to quantify the financial performance of seven organizations listed on the Egyptian Stock Exchange in 2007-2014. Then uses the information retrieval technologies to quantify the contribution of each of the three dimensions of the corporate social responsibility report (environmental, social and economic). Finally, the correlation between these two sets of variables is viewed together in a model to detect the correlations between them. This model is applied on seven firms that generate social responsibility reports. The results show a positive correlation between the Earnings per share (market based measure) and the economical dimension in the CSR report. On the other hand, total assets and property, plant and equipment (accounting-based measure) are positively correlated to the environmental and social dimensions of the CSR reports. While there is not any significant relationship between ROA, ROE, Operating income and corporate social responsibility. This study contributes to the literature by providing more clarification of the relationship between CFP and the isolated CSR activities in a developing country.

Keywords: financial, social, machine learning, corporate social performance, corporate social responsibility

Procedia PDF Downloads 293
8839 Effect of Aquatic and Land Plyometric Training on Selected Physical Fitness Variables in Intercollegiate Male Handball Players

Authors: Nisith K. Datta, Rakesh Bharti

Abstract:

The purpose of the study was to find out the effects of Aquatic and Land plyometric training on selected physical variables in intercollegiate male handball players. To achieve this purpose of the study, forty five handball players of Sardar Vallabhbhai National Institute of Technology, Surat, Gujarat were selected as players at random and their age ranged between 18 to 21 years. The selected players were divided into three equal groups of fifteen players each. Group I underwent Aquatic plyometric training, Group II underwent Land plyometric training and Group III Control group for three days per week for twelve weeks. Control Group did not participate in any special training programme apart from their regular activities as per their curriculum. The following physical fitness variables namely speed; leg explosive power and agility were selected as dependent variables. All the players of three groups were tested on selected dependent variables prior to and immediately after the training programme. The analysis of covariance was used to analyze the significant difference, if any among the groups. Since, three groups were compared, whenever the obtained ‘F’ ratio for adjusted post test was found to be significant, the Scheffe’s test to find out the paired mean differences, if any. The 0.05 level of confidence was fixed as the level of significance to test the ‘F’ ratio obtained by the analysis of covariance, which was considered as an appropriate. The result of the study indicates due to Aquatic and Land plyometric training on speed, explosive power, and agility has been improved significantly.

Keywords: aquatic training, explosive power, plyometric training, speed

Procedia PDF Downloads 378
8838 Career Decision-Making Difficulty and Emotional Quotient: Basis for a Career Guidance Intervention for City College of Angeles

Authors: Rhenan D. Estacio

Abstract:

This research presents the career decision making difficulty and emotional quotient of one hundred fifty (150) college students of City College of Angeles, Academic Year 2016-2017. Independent sample T-test and Pearson r correlation were done to shifter and non-shifter in terms of their career decision making difficulty and emotional quotient. A significant positive correlation revealed (r=.302) on career decision making difficulty and emotional quotient. Also, a significant negative correlation revealed (r=-.329) on career decision making difficulty and a moderating variable which is age. The finding significantly shows that emotional quotient was associated and adds a significant incremental variance with career decision making difficulty. Moreover, age shows a moderating effect on career decision making difficulty by having a significant decline and increment on variables. Furthermore, categorization of career decision making difficulty and emotional quotient of said participants are described in this study. In addition, career guidance interventions were suggested based on the results of this study.

Keywords: career, decision-making, difficulty, emotional, quotient

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8837 Depression among University Students an Epidemiological Study on a Sample of University Students

Authors: Laid Fekih

Abstract:

Background: Depression affects people in all communities across the world and in all aspects of their lives. Its spread varies from one country to another, can happen at any age and get rid of it is not easy. There is no clear policy in Algeria's higher education institutions to detect and treat these disorders or pay particular attention to those at risk. Identifying the prevalence of depression among Algerian students, its correlation with different variables, and studying gender differences in the light of a range of variables is necessary to develop an appropriate plan to raise the level of hope and love of life among students. Method: Random samples of 1500 University of Tlemcen students (967 girls and 533 boys), aged 19 to 24 years completed a self-administered questionnaire that included Beck's Depression Inventory ®-II (BDI®-II), (School Health Promotion: The Mood part), Other questions included in this survey focused on demographic characteristics including gender, age and year of study, academic performance (Annual Average Score (0-20) AAS), were examined. Results: The rate of depression (moderate, severe and extreme) varied from 03% to 13% among university students in Tlemcen University. There was no difference in the rates of depression in male and female students, which means that male and female students do have similar rates of depression. The rate of depression in the first-year of the study shows a higher score relative to students of other years. Depression has a negative relationship with academic performance, which means that depressed students have many difficulties in academic tasks at university. Conclusion: Depression among university students is an important center of interest in the world, not only because of the ease with which they can be followed, or the difficulties encountered during their studies and their technical courses but for the link between the level of depression and the quality of care of mental health services, especially if many students with mood and emotional problems don't meet the criteria for psychotherapy.

Keywords: depression, epidemiology, university students, academic performance

Procedia PDF Downloads 125
8836 The Impact of Socio-Economic and Type of Religion on the Behavior of Obedience among Arab-Israeli Teenagers

Authors: Sadhana Ghnayem

Abstract:

This article examines the relationship between several socio-economic and background variables of Arab-Israeli families and their effect on the conflict management style of forcing, where teenage children are expected to obey their parents without questioning. The article explores the inter-generational gap and the desire of Arab-Israeli parents to force their teenage children to obey without questioning. The independent variables include: the sex of the parent, religion (Christian or Muslim), income of the parent, years of education of the parent, and the sex of the teenage child. We use the dependent variable of “Obedience Without Questioning” that is reported twice: by each of the parents as well as by the children. We circulated a questionnaire and collected data from a sample of 180 parents and their adolescent child living in the Galilee area during 2018. In this questionnaire we asked each of the parent and his/her teenage child about whether the latter is expected to follow the instructions of the former without questioning. The outcome of this article indicates, first, that Christian-Arab families are less authoritarian than Muslims families in demanding sheer obedience from their children. Second, female parents indicate more than male parents that their teenage child indeed obeys without questioning. Third, there is a negative correlation between the variable “Income” and “Obedience without Questioning.” Yet, the regression coefficient of this variable is close zero. Fourth, there is a positive correlation between years of education and obedience reported by the children. In other words, more educated parents are more likely to demand obedience from their children.  Finally, after running the regression, the study also found that the impact of the variables of religion as well as the sex of the child on the dependent variable of obedience is also significant at above 95 and 90%, respectively.

Keywords: conflict, religion, conflict management style, obedience

Procedia PDF Downloads 154
8835 Investigation of Compressive Strength of Fly Ash-Based Geopolymer Bricks with Hierarchical Bayesian Path Analysis

Authors: Ersin Sener, Ibrahim Demir, Hasan Aykut Karaboga, Kadir Kilinc

Abstract:

Bayesian methods, which have very wide range of applications, are implemented to the data obtained from the production of F class fly ash-based geopolymer bricks’ experimental design. In this study, dependent variable is compressive strength, independent variables are treatment type (oven and steam), treatment time, molding time, temperature, water absorbtion ratio and density. The effect of independent variables on compressive strength is investigated. There is no difference among treatment types, but there is a correlation between independent variables. Therefore, hierarchical Bayesian path analysis is applied. In consequence of analysis we specified that treatment time, temperature and density effects on compressive strength is higher, molding time, and water absorbtion ratio is relatively low.

Keywords: experimental design, F class fly ash, geopolymer bricks, hierarchical Bayesian path analysis

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8834 Association of Photosynthetic Pigment with Oceanic Physical Parameters in the North-eastern Bay of Bengal

Authors: Saif Khan Sunny, Md. Masud-ul-alam

Abstract:

This study presents the association of photosynthetic pigment: chlorophyll-a (chl-a) and physical parameters: sea surface temperature (SST), dissolved oxygen (DO), sea surface salinity (SSS), and total dissolved solids (TDS) in the northeastern Bay of Bengal. At 15 sampling stations in the bay near the eastern coast of Teknaf, photosynthetic pigment and environmental variables were measured for surface water where acetone extraction was used for ch-a. Samples of seawater were taken in March 2021, where chlorophyll-a content varies from 0.554 to 9.696 mg/m3 in surface water over the sampling site. Higher concentrations may be attributable to the nutrient supply of hatcheries and the delivery of fluvial input. The observed SST, DO, SSS, and TDS in the north-eastern Bay of Bengal are 26.65 to 28.6 °C, 6.26 to 8.03 mg/l, 29.3 to 33.1 PSU, and 22.4 to 25.3 ppm, respectively. Temperature and chl-a had a positive association (0.18), according to an analysis of the cross-correlation matrix. Again, a negative correlation (0.34) between dissolved oxygen and temperature is significant at p < 0.05. Total dissolved solids and dissolved oxygen have a significant negative correlation (0.70) where p is < 0.001.

Keywords: photosynthetic pigment, nutrient supply, chlorophyll, physical parameters

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8833 Studying the Effects of Economic and Financial Development as Well as Institutional Quality on Environmental Destruction in the Upper-Middle Income Countries

Authors: Morteza Raei Dehaghi, Seyed Mohammad Mirhashemi

Abstract:

The current study explored the effect of economic development, financial development and institutional quality on environmental destruction in upper-middle income countries during the time period of 1999-2011. The dependent variable is logarithm of carbon dioxide emissions that can be considered as an index for destruction or quality of the environment given to its effects on the environment. Financial development and institutional development variables as well as some control variables were considered. In order to study cross-sectional correlation among the countries under study, Pesaran and Friz test was used. Since the results of both tests show cross-sectional correlation in the countries under study, seemingly unrelated regression method was utilized for model estimation. The results disclosed that Kuznets’ environmental curve hypothesis is confirmed in upper-middle income countries and also, financial development and institutional quality have a significant effect on environmental quality. The results of this study can be considered by policy makers in countries with different income groups to have access to a growth accompanied by improved environmental quality.

Keywords: economic development, environmental destruction, financial development, institutional development, seemingly unrelated regression

Procedia PDF Downloads 330
8832 Estimation of Population Mean under Random Non-Response in Two-Occasion Successive Sampling

Authors: M. Khalid, G. N. Singh

Abstract:

In this paper, we have considered the problems of estimation for the population mean on current (second) occasion in two-occasion successive sampling under random non-response situations. Some modified exponential type estimators have been proposed and their properties are studied under the assumptions that the number of sampling unit follows a discrete distribution due to random non-response situations. The performances of the proposed estimators are compared with linear combinations of two estimators, (a) sample mean estimator for fresh sample and (b) ratio estimator for matched sample under the complete response situations. Results are demonstrated through empirical studies which present the effectiveness of the proposed estimators. Suitable recommendations have been made to the survey practitioners.

Keywords: modified exponential estimator, successive sampling, random non-response, auxiliary variable, bias, mean square error

Procedia PDF Downloads 337
8831 Numerical Study of Natural Convection Heat Transfer Performance in an Inclined Cavity: Nanofluid and Random Temperature

Authors: Hicham Salhi, Mohamed Si-Ameur, Nadjib Chafai

Abstract:

Natural convection of a nanofluid consisting of water and nanoparticles (Ag or TiO2) in an inclined enclosure cavity, has been studied numerically, heated by a (random temperature, based on the random function). The governing equations are solved numerically using the finite-volume. Results are presented in the form of streamlines, isotherms, and average Nusselt number. In addition, a parametric study is carried out to examine explicitly the volume fraction effects of nanoparticles (Ψ= 0.1, 0.2), the Rayleigh number (Ra=103, 104, 105, 106),the inclination angle of the cavity( égale à 0°, 30°, 45°, 90°, 135°, 180°), types of temperature (constant ,random), types of (NF) (Ag andTiO2). The results reveal that (NPs) addition remarkably enhances heat transfer in the cavity especially for (Ψ= 0.2). Besides, the effect of inclination angle and type of temperature is more pronounced at higher Rayleigh number.

Keywords: nanofluid, natural convection, inclined cavity, random temperature, finite-volume

Procedia PDF Downloads 270
8830 Observational Study Reveals Inverse Relationship: Rising PM₂.₅ Concentrations Linked to Decreasing Muon Flux

Authors: Yashas Mattur, Jensen Coonradt

Abstract:

Muon flux, the rate of muons reaching Earth from the atmosphere, is impacted by various factors such as air pressure, temperature, and humidity. However, the influence of concentrations of PM₂.₅ (particulate matter with diameters 2.5 mm or smaller) on muon detection rates remains unexplored. During the summer of 2023, smoke from Canadian wildfires (containing significant amounts of particulate matter) blew over regions in the Northern US, introducing huge fluctuations in PM₂.₅ concentrations, thus inspiring our experiment to investigate the correlation of PM₂.₅ concentrations and muon rates. To investigate this correlation, muon collision rates were measured and analyzed alongside PM₂.₅ concentration data over the periods of both light and heavy smoke. Other confounding variables, including temperature, humidity, and atmospheric pressure, were also considered. The results reveal a statistically significant inverse correlation between muon flux and PM₂.₅ concentrations, indicating that particulate matter has an impact on the rate of muons reaching the earth’s surface.

Keywords: Muon Flux, atmospheric effects on muons, PM₂.₅, airborne particulate matter

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8829 Random Subspace Ensemble of CMAC Classifiers

Authors: Somaiyeh Dehghan, Mohammad Reza Kheirkhahan Haghighi

Abstract:

The rapid growth of domains that have data with a large number of features, while the number of samples is limited has caused difficulty in constructing strong classifiers. To reduce the dimensionality of the feature space becomes an essential step in classification task. Random subspace method (or attribute bagging) is an ensemble classifier that consists of several classifiers that each base learner in ensemble has subset of features. In the present paper, we introduce Random Subspace Ensemble of CMAC neural network (RSE-CMAC), each of which has training with subset of features. Then we use this model for classification task. For evaluation performance of our model, we compare it with bagging algorithm on 36 UCI datasets. The results reveal that the new model has better performance.

Keywords: classification, random subspace, ensemble, CMAC neural network

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8828 Modeling Biomass and Biodiversity across Environmental and Management Gradients in Temperate Grasslands with Deep Learning and Sentinel-1 and -2

Authors: Javier Muro, Anja Linstadter, Florian Manner, Lisa Schwarz, Stephan Wollauer, Paul Magdon, Gohar Ghazaryan, Olena Dubovyk

Abstract:

Monitoring the trade-off between biomass production and biodiversity in grasslands is critical to evaluate the effects of management practices across environmental gradients. New generations of remote sensing sensors and machine learning approaches can model grasslands’ characteristics with varying accuracies. However, studies often fail to cover a sufficiently broad range of environmental conditions, and evidence suggests that prediction models might be case specific. In this study, biomass production and biodiversity indices (species richness and Fishers’ α) are modeled in 150 grassland plots for three sites across Germany. These sites represent a North-South gradient and are characterized by distinct soil types, topographic properties, climatic conditions, and management intensities. Predictors used are derived from Sentinel-1 & 2 and a set of topoedaphic variables. The transferability of the models is tested by training and validating at different sites. The performance of feed-forward deep neural networks (DNN) is compared to a random forest algorithm. While biomass predictions across gradients and sites were acceptable (r2 0.5), predictions of biodiversity indices were poor (r2 0.14). DNN showed higher generalization capacity than random forest when predicting biomass across gradients and sites (relative root mean squared error of 0.5 for DNN vs. 0.85 for random forest). DNN also achieved high performance when using the Sentinel-2 surface reflectance data rather than different combinations of spectral indices, Sentinel-1 data, or topoedaphic variables, simplifying dimensionality. This study demonstrates the necessity of training biomass and biodiversity models using a broad range of environmental conditions and ensuring spatial independence to have realistic and transferable models where plot level information can be upscaled to landscape scale.

Keywords: ecosystem services, grassland management, machine learning, remote sensing

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8827 Prevalance and Factors Associated with Domestic Violence among Preganant Women in Southwest Ethiopia

Authors: Bediru Abamecha

Abstract:

Background: Domestic violence is a global problem that occurs regardless of culture, ethnicity or socio-economic class. It is known to be responsible for numerous hospital visits undertaken by women. Violence on pregnant women is a health and social problem that poses particular risks to the woman and her unborn child. Objective: The Objective of this study will be to assess prevalence of domestic violence and its correalates among pregnant women in Manna Woreda of Jimma Zone. Methods: Simple Random Sampling technique will be used to select 12 kebeles (48% of the study area) and Systematic Sampling will be used to reach to the house hold in selected kebeles in manna woreda of Jimma zone, south west Ethiopia from february 15-25, 2011. An in-depth interview will be conducted on Women affairs, police office and Nurses working and minimum of 4FGD with 6-8 members on pregnant women and selected male from the community. SPSS version 16.0 will be used to enter, clean and analyze the data. Descriptive statistics such as mean or median for continuous variables and percent for categorical variables will be made. Bivariate analysis will be used to check the association between independent variables and domestic violence. Variables found to have association with domestic violence will be entered to multiple logistic regressions for controlling the possible effect of confounders and finally the variables which had significance association will be identified on basis of OR, with 95% CI. All statistical significance will be considered at p<0.05. The qualitative data will be summarized manually and thematic analysis will be performed and finally both will be triangulated.

Keywords: ante natal care, ethiopian demographic and health survey, domestic violence, statistical package for social science

Procedia PDF Downloads 492
8826 The Role of Family’s Emotional Climate and Emotional Expression Style in Academic Well-Being of Students with Military Parent

Authors: Ala Rakhshandeh, Zahra Ashkar, Solmaz Dehghani Dolatabadi, Hossein Bayat

Abstract:

The present study has been conducted to investigate the role of family emotional climate and emotional expression style in the academic well-being of students with military parents. Children, including 280 female students of Shahriar police officers, were selected by random sampling method, and they have been investigated through Alfred B. Hillburn's family emotional climate questionnaire (1964), King and Ammon's emotional expression questionnaire (1990), and Pitrinen, Sweeney, and Falto's academic well-being questionnaire (2014). The data were analyzed using statistical methods of correlation coefficient and stepwise multiple regression under the SPSS23 program. The results reveal that the variables of family emotional climate and emotional expression can explain 36.4% of the variance in academic well-being. This finding reveals that with an increase of standard deviation on the scores of family emotional climate and emotional expression, 0.513 and 0.155 standard deviations are added to the scores of academic well-being, respectively. The emotional climate of the family has a superior distinctive role in predicting the educational well-being of female students. Thus, the emotional climate of the family and the style of emotional expression play a meaningful role in the academic well-being of students with the military parent.

Keywords: emotional climate, family, emotional expression style, academic well-being

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8825 Examination of Public Hospital Unions Technical Efficiencies Using Data Envelopment Analysis and Machine Learning Techniques

Authors: Songul Cinaroglu

Abstract:

Regional planning in health has gained speed for developing countries in recent years. In Turkey, 89 different Public Hospital Unions (PHUs) were conducted based on provincial levels. In this study technical efficiencies of 89 PHUs were examined by using Data Envelopment Analysis (DEA) and machine learning techniques by dividing them into two clusters in terms of similarities of input and output indicators. Number of beds, physicians and nurses determined as input variables and number of outpatients, inpatients and surgical operations determined as output indicators. Before performing DEA, PHUs were grouped into two clusters. It is seen that the first cluster represents PHUs which have higher population, demand and service density than the others. The difference between clusters was statistically significant in terms of all study variables (p ˂ 0.001). After clustering, DEA was performed for general and for two clusters separately. It was found that 11% of PHUs were efficient in general, additionally 21% and 17% of them were efficient for the first and second clusters respectively. It is seen that PHUs, which are representing urban parts of the country and have higher population and service density, are more efficient than others. Random forest decision tree graph shows that number of inpatients is a determinative factor of efficiency of PHUs, which is a measure of service density. It is advisable for public health policy makers to use statistical learning methods in resource planning decisions to improve efficiency in health care.

Keywords: public hospital unions, efficiency, data envelopment analysis, random forest

Procedia PDF Downloads 111