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Utilizing data from two large samples, cognitive variables were evaluated as potential mediators of the past crime–future crime relationship. In the first study, the reconstructed General Criminal Thinking (GCTrc) score of the Psychological Inventory of Criminal Thinking Styles (PICTS) was found to mediate the relationship between past adult convictions/juvenile adjudications and future recidivism in 1,101 male federal prisoners. In the second study, a cognitive appraisal of one’s future chances of arrest was found to mediate the relationship between self-reported delinquency between the ages of 13 and 15 and self-reported delinquency between the ages of 17 and 19 in 1,414 male and female members of the 1997 National Longitudinal Survey of Youth (NLSY) cohort. Sensitivity analysis revealed that the mediating effects in both studies were reasonably robust to violations of the sequential ignorability assumption. These findings suggest that cognitive factors may play a role in encouraging continuity from the early to the later stages of criminal involvement. © The Author(s) 2013. Source


Kelley K.J.,Pennsylvania State University | Gruber E.M.,Kutztown University
Computers in Human Behavior | Year: 2010

Several instruments have been designed to measure problems associated with excessive, compulsive, or addictive use of the Internet. One such instrument, the 18-item Problematic Internet Use Questionnaire, was recently published with data supporting a three subscale model (Demetrovics et al., 2008). These researches utilized an online format with a sample taken from the general population of Hungary. We utilized an American college student sample and a paper and pencil format to perform a confirmatory factor analysis of the PIUQ. In addition, we examined the reliability and construct validity of the PIUQ by examining the scales' relationship with several indices of psychological and physical health. CFA results indicate a barely adequate and not completely problem free three factor model for the PIUQ (χ 2 = 477.40; root mean square error = .097; comparative fit index = .831; Tucker Lewis coefficient = .804). Cronbach's α for the total scale was .91 while the Cronbach's α for each subscale were .81, .77, and .79. Construct validity for the model is demonstrated with significant correlations between the subscales and several indices of psychological and physical health. Suggestions for further research are provided. © 2010 Elsevier Ltd. All rights reserved. Source


Wang W.-P.,Nanjing Southeast University | Yang Z.-M.,Nanjing Southeast University | Yang Z.-M.,Nanjing University of Information Science and Technology | Zhang B.,Nanjing University of Information Science and Technology | And 2 more authors.
Proceedings of IEEE International Conference on Grey Systems and Intelligent Services, GSIS | Year: 2015

In this paper, we will expand the industrial ecosystem to three subsystems: the economy subsystem, the environment subsystem, and the innovation subsystem. Based on principal component analysis and grey correlation analysis, a model of the optimizing degree of Chinese economic industrial ecosystem is developed at the provincial level, and a mathematical definition of the optimization degree is provided to evaluate the provincial industrial ecosystem from a relatively new perspective. Based on their optimization degrees, the thirty provinces of China are classified into four categories in terms of their economy-environment-innovation relation: the harmonious region, the gearing region, the rivaling region and the discordant region. By fitting the curve of Environment Kuznets Curve (EKC) with a cubic function for each category, we show that each category has its own shape of EKC: category I has the monotonically decreasing curve, category II has a inverted U shaped curve, category III has a N-shaped curve, while category IV has a U-shaped curve. Our results show how the category's optimization degree of industrial ecosystem affects the relation of economic growth to environmental quality. In particular, for the region I whose optimization degree γ>0.7, the relation between economic growth and environmental pollutants is harmonious; for the region II whose optimization degree 0.6<γ<0.7, the relation is rivaling; for the region III whose optimization degree 0.5<γ<0.6, the relation is conflicting; and for the region IV whose optimization degree γ<0.5, the relation is discordant. © 2015 IEEE. Source


Frye L.,Kutztown University | Frye L.,Lehigh University | Cheng L.,Lehigh University
GLOBECOM - IEEE Global Telecommunications Conference | Year: 2010

Network management is a critical component of every network manager's job responsibility. This job gets more complicated as the complexity of the network grows. This complexity can be in the form of different manufacturers of deployed devices or added tiers to the network, such as an Ad Hoc Network or a Wireless Sensor Network. Automating, or semi-automating, the data analysis required in network management will decrease the complexity of managing these heterogeneous, multi-tier networks. Incorporating ontology into a network management system can assist the management of a heterogeneous, multi-tier network and reduce the management complexity. A new Network Management System that utilizes ontology has been developed to assist the network management, specifically topology discovery, of a heterogeneous, multi-tier network. Simulation results show that the overhead of using ontology overhead in the new Network Management System is acceptable given the inherent benefits. ©2010 IEEE. Source


Walters G.D.,Kutztown University | Noon A.,Kutztown University
Journal of Interpersonal Violence | Year: 2015

The purpose of this study was to determine whether childhood animal cruelty is primarily a feature of family context or of externalizing behavior. Twenty measures of family context and proactive (fearlessness) and reactive (disinhibition) externalizing behavior were correlated with the retrospective accounts of childhood animal cruelty provided by 1,354 adjudicated delinquents. A cross-sectional analysis revealed that all 20 family context, proactive externalizing, and reactive externalizing variables correlated significantly with animal cruelty. Prospective analyses showed that when the animal cruelty variable was included in a regression equation with the 10 family context variables (parental arguing and fighting, parental drug use, parental hostility, and parental knowledge and monitoring of offspring behavior) or in a regression equation with the five reactive externalizing variables (interpersonal hostility, secondary psychopathy, weak impulse control, weak suppression of aggression, and short time horizon), it continued to predict future violent and income (property + drug) offending. The animal cruelty variable no longer predicted offending, however, when included in a regression equation with the five proactive externalizing variables (early onset behavioral problems, primary psychopathy, moral disengagement, positive outcome expectancies for crime, and lack of consideration for others). These findings suggest that while animal cruelty correlates with a wide range of family context and externalizing variables, it may serve as a marker of violent and nonviolent offending by virtue of its position on the proactive subdimension of the externalizing spectrum. © The Author(s) 2014 Source

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