<Emphasis Type="BoldItalic">MAD-STEC</Emphasis>: a method for multiple automatic detection of space-time emerging clusters

Crime or disease surveillance commonly rely in space-time clustering methods to identify emerging patterns. The goal is to detect spatial-temporal clusters as soon as possible after its occurrence and to control the rate of false alarms. With this in mind, a spatio-temporal multiple cluster detection method was developed as an extension of a previous proposal based on a spatial version of the Shiryaev–Roberts statistic. Besides the capability of multiple cluster detection, the method have less input parameter than the previous proposal making its use more intuitive to practitioners. To evaluate the new methodology a simulation study is performed in several scenarios and enlighten many advantages of the proposed method. Finally, we present a case study to a crime data-set in Belo Horizonte, Brazil.     

Fast parallel $$\alpha $$-stable distribution function evaluation and parameter estimation using OpenCL in GPGPUs

\(\alpha \)-Stable distributions are a family of probability distributions found to be suitable to model many complex processes and phenomena in several research fields, such as medicine, physics, finance and networking, among others. However, the lack of closed expressions makes their evaluation analytically intractable, and alternative approaches are computationally expensive. Existing numerical programs are not fast enough for certain applications and do not make use of the parallel power of general purpose graphic processing units. In this paper, we develop novel parallel algorithms for the probability density function and cumulative distribution function—including a parallel Gauss–Kronrod quadrature—, quantile function, random number generator and maximum likelihood estimation of \(\alpha \)-stable distributions using OpenCL, achieving significant speedups and precision in all cases. Thanks to the use of OpenCL, we also evaluate the results of our library with different GPU architectures.     

$$D_s$$-optimality in copula models

Optimum experimental design theory has recently been extended for parameter estimation in copula models. The use of these models allows one to gain in flexibility by considering the model parameter set split into marginal and dependence parameters. However, this separation also leads to the natural issue of estimating only a subset of all model parameters. In this work, we treat this problem with the application of the \(D_s\)-optimality to copula models. First, we provide an extension of the corresponding equivalence theory. Then, we analyze a wide range of flexible copula models to highlight the usefulness of \(D_s\)-optimality in many possible scenarios. Finally, we discuss how the usage of the introduced design criterion also relates to the more general issue of copula selection and optimal design for model discrimination.     

Giving Victims of Bullying a Voice: A Qualitative Study of Post Bullying Reactions and Coping Strategies

Current research on how adolescents cope with bullying is primarily quantitative, examines youth in Grades 1 through 6, and neglects to specifically assess how victims of bullying cope with being bullied. The current qualitative study explored the coping strategies of 22 rural middle- and high-school youth victimized by bullying. Results indicated that youth report using an array of emotion focused coping strategies (an internal coping strategy that focuses on emotion regulation) and problem focused coping strategies (active behaviors that are aimed to decrease or eradicate the stressor). These coping strategies included help seeking, physical and verbal aggression, standing up for themselves, and prosocial bystander behavior. While the majority of coping strategies were similar between middle- and high-school participants, these groups reported utilizing verbal and physical aggression in different ways. Further, certain coping strategies, such as help seeking and lashing out with physical and verbal aggression, were utilized as both emotion- and problem-focused coping strategies. Implications are discussed.     

Cyberbullying on Online Gaming Platforms for Children and Youth

Cyberbullying has been recognized as a serious social concern. Considering the varied contexts of online engagement by children and youth is increasingly necessary to adequately understand their experiences and the impact of their participation. An online context which requires further attention is gaming platforms, which are especially popular among boys. Methods: Using a theoretical approach of social dominance, this paper analyzed secondary data drawn from a mixed methods study of cyberbullying to investigate the prevalence and experience of gaming among a quantitative survey sample (n?=?670) of 4th, 7th, and 10th grade students, as well as the experience and impact of gaming on a qualitative interview sub-sample (n?=?57). Gaming prevalence rates are provided. Boys were significantly more likely to engage in internet gaming (though the effect size was small); χ² (1, n?=?669)?=?10.11, p?=?0.001, phi?=??0.123, 95% CI (?0.207, ?0.047). Qualitative content analysis (QCA) identified four themes: (1) aggression (exceeding what was required to achieve game objectives) characterized gaming culture and pervaded gaming platforms; (2) anonymity contributed to the culture of aggression; (3) participants often did not consider aggression cyberbullying, but rather just a part of the culture of gaming platforms; and (4) participants’ responses to aggressive behaviors. Certain behaviors on gaming platforms may not be appropriately recognized as cyberbullying. Implications for social work practice with children and youth are provided.     

Empirical Application of Skinner’s Verbal Behavior to Interventions for Children with Autism: A Review

The Analysis of Verbal Behavior - Sundberg and Michael (2011) reviewed the contributions of Skinner’s (1957) Verbal Behavior to the treatment of language delays in children with autism...     

Using clinical signs of neglect to identify elder neglect cases

Elder neglect is the one of the most pervasive forms of mistreatment, and often the only place outside of the individual’s residence to identify and assist neglected individuals is in a medical setting. However, elder neglect cases treated in hospitals do not present with a single diagnosis or clinical sign, but rather involve a complex constellation of clinical signs. Currently, there is a lack of comprehensive guidelines on which clinical signs to use in screening tools for neglect among patients treated in hospitals. Using the DELPHI method, a group of experts developed and tested a scale to be used as a pre-screener that conceptually could be integrated into electronic health record systems so that it could identify potential neglect cases in an automated manner. By applying the scale as a pre-screener for neglect, the tool would reduce the pool of at-risk patients who would benefit from in-depth screening for elder neglect by 95%.