scholarly journals Are Professional Burnout and Work Engagement Opposing or Independent Constructs?

2021 ◽  
Vol 23 (3) ◽  
pp. 291-307
Author(s):  
Bohdan Rożnowski
Keyword(s):  
Regression Analysis ◽  
Work Engagement ◽  
Statistical Analyses ◽  
One Dimension ◽  
Professional Burnout ◽  
Mutual Relationship ◽  
Work Situation ◽  
Lively Discussion ◽  
Different Types ◽  
Different Sources

The aim of the article is to broaden the knowledge about the mutual relationship between work engagement and professional burnout. In the psychological literature, a lively discussion between the position that these are opposite poles of one dimension and the position that both dimensions are independent has not yet been clearly concluded. The article focuses on the analysis of the causes of both phenomena. It was assumed that one-dimensionality means that the same elements of the work situation affect each of the states but in an opposite way. The research was conducted using standardized questionnaires (AWLS, LBQ, and UWES) on a group of 128 teachers from different types of schools. Statistical analyses relying on regression analysis indicated different sources of each phenomenon, which supports the position of independence of both constructs.

scholarly journals How to measure uncertainty in uncertainty sampling for active learning

2021 ◽  
Author(s):  
Vu-Linh Nguyen ◽  
Mohammad Hossein Shaker ◽  
Eyke Hüllermeier
Keyword(s):  
Machine Learning ◽  
Active Learning ◽  
Sampling Strategies ◽  
Total Uncertainty ◽  
Uncertainty Sampling ◽  
Different Types ◽  
Alternative Approaches ◽  
Active Learner ◽  
Probabilistic Nature ◽  
Different Sources

AbstractVarious strategies for active learning have been proposed in the machine learning literature. In uncertainty sampling, which is among the most popular approaches, the active learner sequentially queries the label of those instances for which its current prediction is maximally uncertain. The predictions as well as the measures used to quantify the degree of uncertainty, such as entropy, are traditionally of a probabilistic nature. Yet, alternative approaches to capturing uncertainty in machine learning, alongside with corresponding uncertainty measures, have been proposed in recent years. In particular, some of these measures seek to distinguish different sources and to separate different types of uncertainty, such as the reducible (epistemic) and the irreducible (aleatoric) part of the total uncertainty in a prediction. The goal of this paper is to elaborate on the usefulness of such measures for uncertainty sampling, and to compare their performance in active learning. To this end, we instantiate uncertainty sampling with different measures, analyze the properties of the sampling strategies thus obtained, and compare them in an experimental study.

scholarly journals Model-Based Probabilistic Inversion Using Magnetic Data: A Case Study on the Kevitsa Deposit

Geosciences ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 150
Author(s):  
Nilgün Güdük ◽  
Miguel de la Varga ◽  
Janne Kaukolinna ◽  
Florian Wellmann
Keyword(s):  
Structural Parameters ◽  
Rock Properties ◽  
Magnetic Data ◽  
Geological Model ◽  
Borehole Data ◽  
Likelihood Functions ◽  
Different Types ◽  
Geophysical Information ◽  
Different Sources

Structural geological models are widely used to represent relevant geological interfaces and property distributions in the subsurface. Considering the inherent uncertainty of these models, the non-uniqueness of geophysical inverse problems, and the growing availability of data, there is a need for methods that integrate different types of data consistently and consider the uncertainties quantitatively. Probabilistic inference provides a suitable tool for this purpose. Using a Bayesian framework, geological modeling can be considered as an integral part of the inversion and thereby naturally constrain geophysical inversion procedures. This integration prevents geologically unrealistic results and provides the opportunity to include geological and geophysical information in the inversion. This information can be from different sources and is added to the framework through likelihood functions. We applied this methodology to the structurally complex Kevitsa deposit in Finland. We started with an interpretation-based 3D geological model and defined the uncertainties in our geological model through probability density functions. Airborne magnetic data and geological interpretations of borehole data were used to define geophysical and geological likelihoods, respectively. The geophysical data were linked to the uncertain structural parameters through the rock properties. The result of the inverse problem was an ensemble of realized models. These structural models and their uncertainties are visualized using information entropy, which allows for quantitative analysis. Our results show that with our methodology, we can use well-defined likelihood functions to add meaningful information to our initial model without requiring a computationally-heavy full grid inversion, discrepancies between model and data are spotted more easily, and the complementary strength of different types of data can be integrated into one framework.

scholarly journals Structural Equation Model of Work Situation and Work–Family Conflict on Depression and Work Engagement in Commercial Motor Vehicle (CMV) Drivers

2021 ◽  
Vol 11 (13) ◽  
pp. 5822
Author(s):  
Dong-Seok Shin ◽  
Byung-Yong Jeong
Keyword(s):  
Structural Equation Model ◽  
Work Engagement ◽  
Family Conflict ◽  
Structural Equation ◽  
Motor Vehicle ◽  
Equation Model ◽  
Work Situation ◽  
Work Family Conflict ◽  
Commercial Motor Vehicle ◽  
Work Family

The shortage and aging of drivers are not problems limited to the truck industry, but are common in the broader commercial motor vehicle (CMV) industry of Korea. This study investigates the relationships between work situation, work–family conflict, depression, and work engagement of taxi, bus, and truck drivers. We extracted 512 CMV drivers from the 5th Korea Working Conditions Survey. A structural equation model (SEM) was used to investigate the impact of a work situation or work–family conflict on depression and work engagement. Results showed that 38.9% of all respondents had symptoms of depression. In the SEM, a poor work situation (standardized path coefficient = 0.250) and work–family conflict (0.117) significantly affected depression. ‘Enough time’ and ‘feeling well’ were influential variables of work situation. ‘Responsibility’ and ‘concentration’ were influential variables of work–family conflict. Additionally, depression affected work engagement (0.524). ‘Vigor’ and ‘dedication’ were influential variables of work engagement. These results show that the relationships between work situation, work–family conflict, depression, and work engagement of CMV drivers are intricately linked.

Canadian Exceptionalism: Explaining Differences over Time in Provincial and Federal Voter Turnout

2001 ◽  
Vol 34 (2) ◽  
pp. 299-319 ◽  
Author(s):  
Donley T. Studlar
Keyword(s):  
Regression Analysis ◽  
Population Density ◽  
Multiple Regression Analysis ◽  
Voter Turnout ◽  
The Political ◽  
Federal Level ◽  
Industrial Democracies ◽  
Different Types ◽  
Over Time ◽  
Cross National

Canada is unusual among advanced industrial democracies in having some provinces which regularly have greater voter turnouts for provincial than for federal elections. Provincial and federal turnouts by province in Canada are analyzed for the 1945-1998 period using multiple regression analysis, both for each set of elections and by comparing differences between the two. Federal turnout has declined over the years but provincial turnout appears to have increased slightly. Although the effects found here largely confirm previous findings about the relative effects of different types of variables found for the Canadian federal level only, several of the political explanations previously supported in cross-national research find less support. Instead, region, population density, months since the last federal or provincial election, and season of the year generally have greater and sometimes more consistent effects. This suggests the need for more studies of turnout in democracies at sub-central levels.

The Behavioral Consequences of Conflict Exposure on Risk Preferences

2021 ◽  
Author(s):  
Enrique Fatas ◽  
Nathaly Jiménez ◽  
Lina Restrepo-Plaza ◽  
Gustavo Rincón
Keyword(s):  
Substantial Effect ◽  
Risk Attitudes ◽  
Behavioral Consequences ◽  
Criminal Violence ◽  
Incentive Compatible ◽  
Attitudinal Factors ◽  
Different Types ◽  
Close Relatives ◽  
Different Sources ◽  
Consequences Of Violence

Violent conflict is a polyhedric phenomenon. Beyond the destruction of physical and human capital and the economic, political, and social costs war generates, there is an additional burden carried by victims: persistent changes in the way they make decisions. Exposure to violence generates changes in how individuals perceive other individuals from their group and other groups, how they discount the future, and how they assess and tolerate risk. The behavioral consequences of violence exposure can be documented using experiments in which participants make decisions in a controlled, incentive-compatible scenario. The external validity of experiments is reinforced when the studies are run in postconflict scenarios, for example, in Colombia, with real victims of conflict. The experimental tasks, therefore, may map risk attitudes among victims and nonvictims of the conflict who share a common background, and distinguish between different types of exposure (direct versus indirect) and different sources of violence (conflict-related versus criminal violence). The experimental evidence collected in Colombia is consistent with a long-lasting and substantial effect of conflict exposure on risk attitudes. Victims are more likely to take risks and less likely to make safe choices than nonvictims, controlling for demographic, socioeconomic, and attitudinal factors. The effect is significant only when the source of violence is conflict (exerted by guerrilla or paramilitary militias) and when violence is experienced directly by individuals. Indirect conflict exposure (suffered by close relatives) and criminal violence leave no significant mark on participants’ risk attitudes in the study.

A Review on Green Synthesis and Applications of Iron Oxide Nanoparticles

2021 ◽  
Vol 21 (12) ◽  
pp. 5812-5834
Author(s):  
Rachana Yadwade ◽  
Saili Kirtiwar ◽  
Balaprasad Ankamwar
Keyword(s):  
Iron Oxide ◽  
Iron Oxide Nanoparticles ◽  
Aqueous System ◽  
Oxide Nanoparticles ◽  
Plant Parts ◽  
Different Types ◽  
Removal Of Heavy Metals ◽  
Biological Sources ◽  
Different Sources

Bio-fabrication of iron oxide nanoparticles by using different sources of plants, plant parts and microbial cells have become a great topic of interest nowadays due to its eco-friendly nature. The stabilizing and capping agents in biological sources are biocompatible, stable and non-toxic which make its use beneficial for various biomedical applications. The bacteria are able to utilize metal ions and convert them into their respective nanoparticles by secreting different biomolecules. The plants and plant parts contain different types of phytochemicals which play a key role in synthesis and bio-fabrication of nanoparticles. Iron oxide nanoparticles are known to have various applications in the fields of medicine, environment etc. This review summarizes the applications of iron oxide nanoparticles as antimicrobial agent, drug delivery agent, material for removal of heavy metals and dyes from aqueous system etc. Due to these wide applications of iron oxide nanoparticles its demand in various fields is increasing considerably. This review describes different approaches which are used for biosynthesis of iron oxide nanoparticles and their applications. The review also summarizes about the surface modification strategies of iron oxide nanoparticles by using different polymers, polyelectrolytes which can be used for in-vivo applications.

Loss of Life and Loss of Bodily Integrity: Two Different Sources of Threat for People who are Ill

1985 ◽  
Vol 15 (3) ◽  
pp. 207-222 ◽  
Author(s):  
Linda L. Viney
Keyword(s):  
Healthy People ◽  
Personal Construct ◽  
Personal Construct Theory ◽  
Bodily Integrity ◽  
Loss Of Life ◽  
Psychological States ◽  
Different Types ◽  
Construct Theory ◽  
Positive Feelings ◽  
Different Sources

Personal construct theory was used to generate some questions about the meanings that different types of threat–loss of life and loss of bodily integrity–hold for people who are severely ill. Content analyses of the responses of ill people and healthy people indicated that ill people expressed more concern with both types of threat than healthy people. Ill people who were suffering from acute rather than chronic illness, who were scheduled for surgery and who were hospitalized rather than being cared for at home expressed more concern about loss of life but not about loss of bodily integrity than other ill people. Each type of threatened loss was found to be associated with a different set of psychological states for people who were ill. Threat of loss of life was associated with indirectly expressed anger and uncertainty but also with the expression of many positive feelings. Threat of loss of bodily integrity was also associated with indirectly expressed anger, but with direct expression of it too, together with hopelessness and helplessness. Patients facing the first threat saw themselves as actively engaged in relationships with others, while those facing the second viewed themselves more often as passive participants. The value of this information about the meanings of threats of loss of life and loss of bodily integrity for the counseling of ill people dealing with these threats was illustrated by two case studies.

scholarly journals The Influence of Architecture Students’ Learning Approaches on their Academic Performance in Two Nigeria Universities

2021 ◽  
Vol 20 (2) ◽  
pp. 137-151
Author(s):  
Gabriel Sen ◽  
Albert Adeboye ◽  
Oluwole Alagbe
Keyword(s):  
Regression Analysis ◽  
Academic Performance ◽  
Deep Learning ◽  
Pilot Study ◽  
Statistical Analyses ◽  
Future Research ◽  
Learning Approaches ◽  
Research Needs ◽  
Heterogeneous Samples ◽  
And Gender

The paper was a pilot study that examined learning approaches of architecture students; variability of approaches by university type and gender and; influence of architecture students’ learning approaches on their academic performance. The sample was 349 architecture students from two universities. Descriptive and statistical analyses were used. Results revealed predominant use of deep learning approaches by students. Furthermore, learning approaches neither significantly differed by university type nor gender. Regression analysis revealed that demographic factors accounted for 2.9% of variation in academic performance (F (2,346) = 6.2, p = 0.002, R2 = 0.029, f2 = 0.029) and when learning approaches were also entered the model accounted for 4.4% of variation in academic performance (F (14,334) =2.2, p =0.009, R2 = 0.044, f2=0.044). Deep learning approaches significantly and positively influenced variation in academic performance while surface learning approaches significantly and negatively influenced academic performance. This implies that architectural educators should use instructional methods that encourage deep approaches. Future research needs to use larger and more heterogeneous samples for confirmation of results.

scholarly journals TERRESTRIAL LASER SCANNERS SELF-CALIBRATION STUDY: DATUM CONSTRAINTS ANALYSES FOR NETWORK CONFIGURATIONS

2015 ◽  
Vol XL-2/W4 ◽  
pp. 1-9 ◽  
Author(s):  
M. A. Abbas ◽  
H. Setan ◽  
Z. Majid ◽  
A. K. Chong ◽  
L. Chong Luh ◽  
...  
Keyword(s):  
Laser Scanner ◽  
Network Configuration ◽  
Calibration Technique ◽  
Self Calibration ◽  
Laser Scanners ◽  
Different Types ◽  
Minimum Number ◽  
Calibration Study ◽  
Different Sources ◽  
Selection Of

Similar to other electronic instruments, terrestrial laser scanner (TLS) can also inherent with various systematic errors coming from different sources. Self-calibration technique is a method available to investigate these errors for TLS which were adopted from photogrammetry technique. According to the photogrammetry principle, the selection of datum constraints can cause different types of parameter correlations. However, the network configuration applied by TLS and photogrammetry calibrations are quite different, thus, this study has investigated the significant of photogrammetry datum constraints principle in TLS self-calibration. To ensure that the assessment is thorough, the datum constraints analyses were carried out using three variant network configurations: 1) minimum number of scan stations; 2) minimum number of surfaces for targets distribution; and 3) minimum number of point targets. Based on graphical and statistical, the analyses of datum constraints selection indicated that the parameter correlations obtained are significantly similar. In addition, the analysis has demonstrated that network configuration is a very crucial factor to reduce the correlation between the calculated parameters.

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