Cyber-Identity Theft and Fintech Services

2021 ◽  
Vol 14 (3) ◽  
pp. 1-19
Author(s):  
Kwame Okwabi Asante-Offei ◽  
Winfred Yaokumah
Keyword(s):  
Significant Relationship ◽  
Regression Models ◽  
Identity Theft ◽  
Intention To Use ◽  
Linear Regression Models ◽  
Financial Loss ◽  
Actual Use ◽  
Threat Avoidance ◽  
The Relationship ◽  
Financial Technology

The fear of identity theft has been considered as an impediment to the rapid utilization of financial technology (FinTech) services. Based on the technology threat avoidance theory (TTAT), this study aims at investigating the willingness of users to use FinTech services notwithstanding the increasing rate of identity theft. This study examines the relationship between the constructs of fear of financial loss, fear of reputational damage, intention to use, and the actual use of FinTech services. Using multiple linear regression models and Pearson's correlation, the results indicate that the fear of financial loss and the fear of reputational damage have no statistical significant relationship with the intention to use and the use of FinTech services. However, the results show a significant relationship between intention to use and the actual use of FinTech services. Consequently, the study indicates that the fear of identity theft does not significantly deter users from using FinTech services.

scholarly journals Relationships between kiwifruit bacterial canker disease and kiwifruit productivity

2014 ◽  
Vol 67 ◽  
pp. 34-40 ◽  
Author(s):  
K.J. Froud ◽  
N. Cogger ◽  
R.M. Beresford
Keyword(s):  
Pseudomonas Syringae ◽  
Significant Relationship ◽  
Regression Models ◽  
Virulent Strain ◽  
Bacterial Canker ◽  
Infection Status ◽  
Linear Regression Models ◽  
Canker Disease ◽  
Productivity Data ◽  
The Relationship

Bacterial canker disease caused by a virulent strain of Pseudomonas syringae pv actinidiae (PsaV) has affected kiwifruit vines in New Zealand since 2010 This study investigated the association of PsaV with productivity within Hayward and Hort16A varieties PsaV infection status and date of diagnosis for 3309 infected orchards were provided by Kiwifruit Vine Health while Zespri provided productivity data Linear regression models were constructed to determine the relationship between production and PsaV infection in Hayward and Hort16A orchards Results showed a significant relationship between the numbers of weeks PsaV was detected in Hort16A orchards and a reduction in productivity This was likely due to the removal of Hort16A vines or productive areas of canopy in response to the presence of severe symptoms within an orchard A similar significant relationship was also found in Hayward orchards although the reduction in productivity was smaller and took longer to develop than in Hort16A

The love of money and the propensity to engage in unethical behaviours: a study in the Portuguese context

2020 ◽  
Vol 33 (3/4) ◽  
pp. 481-499
Author(s):  
Filipa Oliveira ◽  
Tânia M.G. Marques
Keyword(s):  
Significant Relationship ◽  
Regression Models ◽  
Linear Regression Models ◽  
Content Type ◽  
Unethical Behaviour ◽  
Final Sample ◽  
Love Of Money ◽  
The Love Of Money ◽  
Negative Feelings ◽  
The Relationship

PurposeThis work aims to study the relationship between individuals' love of money and their propensity to engage in unethical behaviour.Design/methodology/approachData were collected through a questionnaire, with the final sample consisting of 297 Portuguese individuals. The hypotheses were tested using linear regression models.FindingsThe results demonstrate that there is no significant relationship between the love of money and the propensity to engage in unethical behaviour. However, there was a significant relationship between the level of budgeting and the propensity to engage in unethical behaviours – for those individuals who have a greater ability to manage their money are less likely to engage in behaviours unethical. The existence of a significant relationship between the “evil” factor and the propensity to engage in unethical behaviour was also validated, which demonstrates that when individuals both associate negative feelings with money and consider love of money to be the “root of evil”, then they are less likely to be involved in unethical behaviour.Originality/valueThis work contributes theoretically and empirically to a better understanding of individuals' attitudes towards money and their propensity to engage in unethical behaviour. The results are of particular academic and organisational relevance due to the implications for human resource management.

Relationship Between Mental Health, Resilience, and Physical Activity in Older Adults: A 2-Year Longitudinal Study

2021 ◽  
pp. 1-9
Author(s):  
Maria Priscila Wermelinger Ávila ◽  
Jimilly Caputo Corrêa ◽  
Alessandra Lamas Granero Lucchetti ◽  
Giancarlo Lucchetti
Keyword(s):  
Mental Health ◽  
Physical Activity ◽  
Older Adults ◽  
Regression Models ◽  
Linear Regression Models ◽  
Physically Active ◽  
Effective Interventions ◽  
Self Sufficiency ◽  
The Relationship

The aim of this study was to longitudinally investigate the association between resilience and mental health in older adults and to determine the influence of physical activity on this relationship. A total of 291 older adults were included in a 2-year follow-up study. Adjusted linear regression models evaluated the association between resilience at baseline and mental health after 2 years in sufficiently and insufficiently physically active older adults. A negative correlation was found between resilience at baseline and depression, anxiety, and stress after 2 years for the overall sample. This association changed after stratifying the group. Sufficiently physically active individuals made greater use of the resilience components “Self-Sufficiency” and “Perseverance,” whereas insufficiently physically active individuals made greater use of “Meaning of Life” and “Existential Singularity.” Physical activity can influence the relationship between resilience and mental health. These results can help guide the devising of more effective interventions for this age group.

scholarly journals Effects of Winter Snow Cover on Spring Soil Moisture Based on Remote Sensing Data Product over Farmland in Northeast China

2020 ◽  
Vol 12 (17) ◽  
pp. 2716
Author(s):  
Shuang Liang ◽  
Xiaofeng Li ◽  
Xingming Zheng ◽  
Tao Jiang ◽  
Xiaojie Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Linear Regression ◽  
Snow Cover ◽  
Snow Depth ◽  
Northeast China ◽  
Regression Models ◽  
Linear Regression Models ◽  
Winter Snow ◽  
The Relationship

Spring soil moisture (SM) is of great importance for monitoring agricultural drought and waterlogging in farmland areas. While winter snow cover has an important impact on spring SM, relatively little research has examined the correlation between winter snow cover and spring SM in great detail. To understand the effects of snow cover on SM over farmland, the relationship between winter snow cover parameters (maximum snow depth (MSD) and average snow depth (ASD)) and spring SM in Northeast China was examined based on 30 year passive microwave snow depth (SD) and SM remote-sensing products. Linear regression models based on winter snow cover were established to predict spring SM. Moreover, 4 year SD and SM data were applied to validate the performance of the linear regression models. Additionally, the effects of meteorological factors on spring SM also were analyzed using multiparameter linear regression models. Finally, as a specific application, the best-performing model was used to predict the probability of spring drought and waterlogging in farmland in Northeast China. Our results illustrated the positive effects of winter snow cover on spring SM. The average correlation coefficient (R) of winter snow cover and spring SM was above 0.5 (significant at a 95% confidence level) over farmland. The performance of the relationship between snow cover and SM in April was better than that in May. Compared to the multiparameter linear regression models in terms of fitting coefficient, MSD can be used as an important snow parameter to predict spring drought and waterlogging probability in April. Specifically, if the relative SM threshold is 50% when spring drought occurs in April, the prediction probability of the linear regression model concerning snow cover and spring SM can reach 74%. This study improved our understanding of the effects of winter snow cover on spring SM and will be beneficial for further studies on the prediction of spring drought.

scholarly journals Association between Cross-Cultural Social Adaptation and Overseas Life Satisfaction among Chinese Medical Aid Team Members (CMATMs) in Africa

2019 ◽  
Vol 16 (9) ◽  
pp. 1572 ◽  
Author(s):  
Xiaochang Chen ◽  
Xiaojun Liu ◽  
Wei Yu ◽  
Anran Tan ◽  
Chang Fu ◽  
...  
Keyword(s):  
Life Satisfaction ◽  
Regression Models ◽  
Cross Cultural ◽  
Social Adaptation ◽  
Linear Regression Models ◽  
Team Members ◽  
Medical Aid ◽  
Electronic Questionnaires ◽  
The Relationship ◽  
Overall Life Satisfaction

This study evaluated the relationship between cross-cultural social adaptation and overseas life satisfaction among Chinese medical aid team members (CMATMs) in Africa. A revised Chinese version of the Sociocultural Adaptation Scale (CSCAS) was used to measure participants’ cross-cultural social adaptation. The self-designed survey of the CMATMs’ overseas life satisfaction includes the following five aspects: food, housing, transportation, entertainment, and security. Electronic questionnaires were distributed non-randomly. Linear regression models were established to explore the association between cross-cultural social adaptation and all dimensions of overseas life satisfaction. After adjusting all the confounders, compared with moderate adaptation, poor adaptation was negatively correlated with all dimensions of overseas life satisfaction (B for food = −0.71, B for housing = −0.76, B for transportation = −0.70, B for entertainment = −0.53, B for security = −0.81, B for overall satisfaction = −0.71, all p < 0.001), whereas good adaptation was positively associated with all dimensions of overseas life satisfaction (B for food = 1.23, B for housing = 1.00, B for transportation = 0.84, B for entertainment = 0.84, B for security = 0.76, B for overall life satisfaction = 0.94, all p < 0.001). This study shows that a better cross-cultural social adaptation was positively connected to a higher level of overseas life satisfaction in general, and more specifically to higher levels of satisfaction with food, housing, transportation, entertainment, and security. This knowledge can be utilized in promoting cross-cultural social adaptation and overseas life satisfaction among CMATMs in Africa.

BAYESIAN IDENTIFICATION OF OUTLIERS AND CHANGE-POINTS IN MEASUREMENT ERROR MODELS

2005 ◽  
Vol 08 (04) ◽  
pp. 433-449 ◽  
Author(s):  
FERNANDO A. QUINTANA ◽  
PILAR L. IGLESIAS ◽  
HELENO BOLFARINE
Keyword(s):  
Linear Regression ◽  
Outlier Detection ◽  
Change Point ◽  
Regression Models ◽  
Point Problem ◽  
Linear Regression Models ◽  
Outlier Identification ◽  
Change Point Problem ◽  
Error In Variables ◽  
The Relationship

The problem of outlier and change-point identification has received considerable attention in traditional linear regression models from both, classical and Bayesian standpoints. In contrast, for the case of regression models with measurement errors, also known as error-in-variables models, the corresponding literature is scarce and largely focused on classical solutions for the normal case. The main object of this paper is to propose clustering algorithms for outlier detection and change-point identification in scale mixture of error-in-variables models. We propose an approach based on product partition models (PPMs) which allows one to study clustering for the models under consideration. This includes the change-point problem and outlier detection as special cases. The outlier identification problem is approached by adapting the algorithms developed by Quintana and Iglesias [32] for simple linear regression models. A special algorithm is developed for the change-point problem which can be applied in a more general setup. The methods are illustrated with two applications: (i) outlier identification in a problem involving the relationship between two methods for measuring serum kanamycin in blood samples from babies, and (ii) change-point identification in the relationship between the monthly dollar volume of sales on the Boston Stock Exchange and the combined monthly dollar volumes for the New York and American Stock Exchanges.

Amendment of traditional assessment measures for the negative symptoms of schizophrenia

2018 ◽  
Vol 49 ◽  
pp. 50-55 ◽  
Author(s):  
Aida Farreny ◽  
Judith Usall ◽  
Jorge Cuevas-Esteban ◽  
Susana Ochoa ◽  
Gildas Brébion
Keyword(s):  
Verbal Memory ◽  
Regression Models ◽  
Negative Symptoms ◽  
Linear Regression Models ◽  
Illness Duration ◽  
Traditional Assessment ◽  
Syndrome Scale ◽  
Assessment Measures ◽  
Negative Syndrome ◽  
The Relationship

AbstractSchizophrenia research based on traditional assessment measures for negative symptoms appears to be, to some extent, unreliable. The limitations of the Positive and Negative Syndrome Scale (PANSS) and the Scale for the Assessment of Negative Symptoms (SANS) have been extensively acknowledged and should be taken into account. The aim of this study is to show how the PANSS and the SANS conflate negative symptoms and cognition and to offer alternatives for the limitations found.MethodsA sample of 117 participants with schizophrenia from two independent studies was retrospectively investigated. Linear regression models were computed to explore the effect of negative symptoms and illness duration as predictors of cognitive performance.ResultsFor the PANSS, the item “abstract thinking” accounted for the association between negative symptoms and cognition. For the SANS, the “attention” subscale predicted the performance in verbal memory, but illness duration emerged as a stronger predictor than negative symptoms for outcomes of processing speed, verbal and working memory.ConclusionUtilizing alternative models to the traditional PANSS and SANS formats, and accounting for illness duration, provide more precise evidence on the relationship between negative symptoms and cognition. Since these measures are still extensively utilized, we recommend adopting more rigorous approaches to avoid misleading results.

scholarly journals Loneliness and COVID-19 preventive behaviours among Japanese adults

2020 ◽  
Author(s):  
Andrew Stickley ◽  
Tetsuya Matsubayashi ◽  
Michiko Ueda
Keyword(s):  
Mental Health ◽  
Logistic Regression ◽  
Odds Ratio ◽  
Regression Models ◽  
Online Survey ◽  
Health Behaviours ◽  
Regression Analyses ◽  
Linear Regression Models ◽  
Japanese Adults ◽  
The Relationship

Abstract Background There is some evidence that loneliness may be linked to poorer health behaviours. Despite this, there has been little research to date on the relationship between loneliness and COVID-19 preventive behaviours. We studied these associations in a sample of the Japanese population. Methods Data were analysed from an online survey of 2000 adults undertaken in April and May 2020. Loneliness was assessed with the Three-Item Loneliness Scale. Information was also collected on 13 COVID-19 preventive behaviours. Regression analyses were used to examine associations. Results In linear regression models adjusted for demographic and mental health variables, both dichotomous and continuous loneliness measures were negatively associated with engaging in COVID-19 preventive behaviours. Logistic regression analyses further showed that loneliness was also associated with reduced odds for a variety of individual preventive behaviours including wearing a mask (odds ratio [OR]: 0.77, 95% confidence interval [CI]: 0.62–0.95), disinfecting hands (OR: 0.80, 95% CI: 0.67–0.94) and social distancing when outdoors (OR: 0.75, 95% CI: 0.61–0.92). Conclusions Loneliness is associated with lower engagement in COVID-19 preventive behaviours. Interventions to prevent or ameliorate loneliness during the ongoing pandemic may be important in combating the spread of the coronavirus.

scholarly journals Temporal-Spatial Analysis of Traffic Congestion Based on Modified CTM

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Chenglong Chu ◽  
Na Xie ◽  
Xiqun Chen ◽  
Yuxin Wu ◽  
Xiaoxiao Sun
Keyword(s):  
Traffic Congestion ◽  
Regression Models ◽  
Piecewise Linear ◽  
Transmission Model ◽  
Spatial Evolution ◽  
Cell Transmission Model ◽  
Linear Regression Models ◽  
Piecewise Linear Regression ◽  
Relationship Of ◽  
The Relationship

A modified cell transmission model (CTM) is proposed to depict the temporal-spatial evolution of traffic congestion on urban freeways. Specifically, drivers’ adaptive behaviors and the corresponding influence on traffic flows are emphasized. Two piecewise linear regression models are proposed to describe the relationship of flow and density (occupancy). Several types of cellular connections are designed to depict urban rapid roads with on/off-ramps and junctions. Based on the data collected on freeway of Queen Elizabeth, Ontario, Canada, we show that the new model provides a relatively higher accuracy of temporal-spatial evolution of traffic congestions.

scholarly journals Factors associated with parasite dominance in fishes from Brazil

2016 ◽  
Vol 25 (2) ◽  
pp. 225-230
Author(s):  
Cristina Fernandes do Amarante ◽  
Wagner de Souza Tassinari ◽  
Jose Luis Luque ◽  
Maria Julia Salim Pereira
Keyword(s):  
Linear Regression ◽  
Body Length ◽  
Regression Models ◽  
Mixed Model ◽  
Multiple Linear Regression Model ◽  
Mixed Effects ◽  
The Body ◽  
Linear Regression Models ◽  
Biological Aspects ◽  
The Relationship

Abstract The present study used regression models to evaluate the existence of factors that may influence the numerical parasite dominance with an epidemiological approximation. A database including 3,746 fish specimens and their respective parasites were used to evaluate the relationship between parasite dominance and biotic characteristics inherent to the studied hosts and the parasite taxa. Multivariate, classical, and mixed effects linear regression models were fitted. The calculations were performed using R software (95% CI). In the fitting of the classical multiple linear regression model, freshwater and planktivorous fish species and body length, as well as the species of the taxa Trematoda, Monogenea, and Hirudinea, were associated with parasite dominance. However, the fitting of the mixed effects model showed that the body length of the host and the species of the taxa Nematoda, Trematoda, Monogenea, Hirudinea, and Crustacea were significantly associated with parasite dominance. Studies that consider specific biological aspects of the hosts and parasites should expand the knowledge regarding factors that influence the numerical dominance of fish in Brazil. The use of a mixed model shows, once again, the importance of the appropriate use of a model correlated with the characteristics of the data to obtain consistent results.

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