176 research outputs found
A MULTILEVEL EXAMINATION OF THE EFFECTS OF NEIGHBORHOOD STRUCTURAL CONDITIONS, PROGRAM AVAILABILITY, AND PROGRAM ATTENDANCE ON PAROLE SUPERVISION OUTCOMES
Between 2008 and 2016 the parole population in the U.S. increased by 44,000 to 870,500 (Kaeble & Cowhig, 2018) and about one third of prison admissions annually are parole violators (Carson, 2015). Participation in programs that address criminogenic needs leads to fewer re-incarcerations (Andrews & Bonta, 2010). Moreover, neighborhood conditions and the availability of programs across neighborhoods are related to returns to prison (Hipp et al., 2010).
This study extends research on parole outcomes by investigating whether neighborhood conditions related to disadvantage negatively affect the number of treatment programs available, the number of program attendances by parolees, and the occurrence of five parole outcomes. Moreover, this study examines the direct effects of program attendance on parole outcomes and whether program attendance moderates the negative effects of community conditions on parole outcomes. Outcomes were examined individually and two groups – outcomes likely to occur early in the parole episode (e.g. violation, positive drug test, violation arrest) and outcomes likely to occur later in the parole episode (e.g., felony arrest, revocation). Both single level and multilevel models were utilized to test hypotheses. The study sample consisted of 1,637 parolees living in 65 census tracts in five urban areas in Georgia who ended supervision between 2011 and 2013.
Findings indicate that among individual level attributes, only parolee risk score predicted all five parole outcomes and being male predicted three of the five parole outcomes. Program attendance predicted an increased likelihood of early outcomes and a reduced likelihood of late outcomes. The number of programs available in a neighborhood did not predict program attendance. Program attendance moderated the effects of several individual level attributes: younger parolees experienced the beneficial effects of program attendance by decreasing the likelihood of felony arrest. Similarly, the beneficial effects of attendance are strengthened for female and white parolees which decreases their likelihood of revocation. None of the neighborhood conditions (level of disadvantage, mobility, or proportion of black population) significantly predicted program attendance. Multi-level analysis examined only the likelihood of early parole outcomes revealing that as a neighborhood’s mobility increased, the likelihood of violation, positive drug test, or violation arrest increased
Simulation of underwater robots using MS Robot Studio©
One stage in designing the control for underwater robot swarms is to confirm the control algorithms via simulation. To perform the simulation Microsoftpsilas Robotic Studiocopy was chosen. The problem with this simulator and others like it is that it is set up for land-based robots only. This paper explores one possible way to get around this limitation. This solution cannot only work for underwater vehicles but aerial vehicles as well.<br /
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Control and simulation of robotic swarms in heterogeneous environments
Simulation provides a low cost method of initial testing of control for robotic swarms. The expansion of robotic swarms to heterogeneous environments drives the need to model cooperative operation in those environments. The Autonomous Control Engineering center at The University of Texas at San Antonio is investigating methods of simulation techniques and simulation environments. This paper presents results from adapting simulation tools for diverse environments.<br /
Investigating how faculty social networks and peer influence relate to knowledge and use of evidence-based teaching practices
Background: Calls for science education reform have been made for decades in the USA. The recent call to produce one million new science, technology, engineering, and math (STEM) graduates over 10 years highlights the need to employ evidence-based instructional practices (EBIPs) in undergraduate STEM classes to create engaging and effective learning environments. EBIPs are teaching strategies that have been empirically demonstrated to positively impact student learning, attitudes, and achievement in STEM disciplines. However, the mechanisms and processes by which faculty learn about and choose to implement EBIPs remain unclear. To explore this problem area, we used social network analysis to examine how an instructor’s knowledge and use of EBIPs may be influenced by their peers within a STEM department. We investigated teaching discussion networks in biology and chemistry departments at three public universities.
Results: We report that tie strength and tie diversity vary between departments, but that mean indegree is not correlated with organizational rank or tenure status. We also describe that teaching discussion ties can often be characterized as strong ties based on two measures of tie strength. Further, we compare peer influence models and find consistent evidence that peer influence in these departments follows a network disturbances model.
Conclusions: Our findings with respect to tie strength and tie diversity indicate that the social network structures in these departments vary in how conducive they might be to change. The correlation in teaching practice between discussion partner and peer influence models suggest that change agents should consider local social network characteristics when developing change strategies. In particular, change agents can expect that faculty may serve as opinion leaders regardless of their academic rank and that faculty can increase their use of EBIPs even if those they speak to about teaching use EBIPs comparatively less
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A SOFTWARE DEFINED NETWORKING ARCHITECTURE FOR HIGH PERFORMANCE CLOUDS 1
ABSTRACT-Multi-tenant clouds with resource virtualization offer elasticity of resources and elimination of initial cluster setup cost and time for applications. However, poor network performance, performance variation and noisy neighbors are some of the challenges for execution of high performance applications on public clouds. Utilizing these virtualized resources for scientific applications, which have complex communication patterns, require low latency communication mechanisms and a rich set of communication constructs. To minimize the virtualization overhead, a novel approach for low latency networking for HPC Clouds is proposed and implemented over a multi-technology software defined network. The efficiency of the proposed low-latency SDN is analyzed and evaluated for high performance applications. The results of the experiments show that the latest Mellanox FDR InfiniBand interconnect and Mellanox OpenStack plugin gives the best performance for implementing virtual machine based high performance clouds with large message sizes
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