Rural Crime and Community Safety

Crime is often perceived as an urban issue rather than a problem that occurs in rural areas, but how far is this view tenable? This book explores the relationship between crime and community in rural areas and addresses the notion of safety as part of the community dynamics in such areas. Rural Crime and Community Safety makes a significant contribution to crime science and integrates a range of theories to understand patterns of crime and perceived safety in rural contexts. Based on a wealth of original research, Ceccato combines spatial methods with qualitative analysis to examine, in detail, farm and wildlife crime, youth related crimes and gendered violence in rural settings. Making the most of the expanding field of Criminology and of the growing professional inquiry into crime and crime prevention in rural areas; rural development; and the social sustainability of rural areas, this book builds a bridge by connecting Criminology and Human Geography. This book will be suitable for academics, students and practitioners in the fields of criminology, community safety, rural studies, rural development and gender studies

Rural Crime and Community Safety

Crime is often perceived as an urban issue rather than a problem that occurs in rural areas, but how far is this view tenable? This book explores the relationship between crime and community in rural areas and addresses the notion of safety as part of the community dynamics in such areas. Rural Crime and Community Safety makes a significant contribution to crime science and integrates a range of theories to understand patterns of crime and perceived safety in rural contexts. Based on a wealth of original research, Ceccato combines spatial methods with qualitative analysis to examine, in detail, farm and wildlife crime, youth related crimes and gendered violence in rural settings. Making the most of the expanding field of Criminology and of the growing professional inquiry into crime and crime prevention in rural areas; rural development; and the social sustainability of rural areas, this book builds a bridge by connecting Criminology and Human Geography. This book will be suitable for academics, students and practitioners in the fields of criminology, community safety, rural studies, rural development and gender studies

Evaluating car-sharing switching rates from traditional transport means through logit models and Random Forest classifiers

Positive impacts of car-sharing, such as reductions in car ownership, congestion, vehicle-miles-traveled and greenhouse gas emissions, have been extensively analyzed. However, these benefits are not fully effective if car-sharing subtracts travel demand from existing sustainable modes. This paper evaluates substitution rates of car-sharing against private cars and public transport using a Random Forest classifier and Binomial Logit model. The models were calibrated and validated using a stated-preference travel survey and applied to a revealed-preference survey, both administered to a representative sample of the population living in Turin (Italy). Results of the two models show that the predictive power of both models is comparable, albeit the Logit model tends to estimate predictions with a higher reliability and the Random Forest model produces higher positive switches towards car-sharing. However, results from both models suggest that the substitution rate of private cars is, on average, almost five times that of public transport

Deep Reinforcement Learning for Black-box Testing of Android Apps

The state space of Android apps is huge, and its thorough exploration during testing remains a significant challenge. The best exploration strategy is highly dependent on the features of the app under test. Reinforcement Learning (RL) is a machine learning technique that learns the optimal strategy to solve a task by trial and error, guided by positive or negative reward, rather than explicit supervision. Deep RL is a recent extension of RL that takes advantage of the learning capabilities of neural networks. Such capabilities make Deep RL suitable for complex exploration spaces such as one of Android apps. However, state-of-the-art, publicly available tools only support basic, Tabular RL. We have developed ARES, a Deep RL approach for black-box testing of Android apps. Experimental results show that it achieves higher coverage and fault revelation than the baselines, including state-of-the-art tools, such as TimeMachine and Q-Testing. We also investigated the reasons behind such performance qualitatively, and we have identified the key features of Android apps that make Deep RL particularly effective on them to be the presence of chained and blocking activities. Moreover, we have developed FATE to fine-tune the hyperparameters of Deep RL algorithms on simulated apps, since it is computationally expensive to carry it out on real apps

Evaluation of dynamic explicit mpm formulations for unsaturated soils

Many applications in geohazards prevention involve large deformations of unsaturated soils, e.g. rainfall induced landslides, embankment collapses due to wetting etc. These phenomena can be investigated with multiphase implementations of the Material Point Method (MPM) able to account for the behaviour of unsaturated soils. This paper compares two formulations: (i) afully coupled three-phase formulation(3P)in which the governing equations are derived from the momentum balance and the mass balance equations of solid, liquid and gas phase assuming non-zero gas pressure,the primary unknowns are the absolute accelerationsof the phases (aS–aL–aG formulation); (ii)a simplified approachthatneglectsthe momentum balance equation of the gas(2P_s).Potentialities and limitations of these approaches are highlighted consideringa 1D infiltration problem.Despite the introduced simplifications, the simplified formulation gives reasonably good results in many engineering cases

Search Based Clustering for Protecting Software with Diversified Updates

Reverse engineering is usually the stepping stone of a variety of attacks aiming at identifying sensitive information (keys, credentials, data, algorithms) or vulnerabilities and flaws for broader exploitation. Software applications are usually deployed as identical binary code installed on millions of computers, enabling an adversary to develop a generic reverse-engineering strategy that, if working on one code instance, could be applied to crack all the other instances. A solution to mitigate this problem is represented by Software Diversity, which aims at creating several structurally different (but functionally equivalent) binary code versions out of the same source code, so that even if a successful attack can be elaborated for one version, it should not work on a diversified version. In this paper, we address the problem of maximizing software diversity from a search-based optimization point of view. The program to protect is subject to a catalogue of transformations to generate many candidate versions. The problem of selecting the subset of most diversified versions to be deployed is formulated as an optimisation problem, that we tackle with different search heuristics. We show the applicability of this approach on some popular Android apps

Crime at the intersection of rail and retail

This chapter examines shoplifting at rail station shops over a 12 month period in England and Wales. Key findings were: shoplifting is concentrated at particular stations; the top 20 stations account for 85% of shoplifting. Clear temporal patterns were evident; shoplifting was higher on weekdays and during holidays with higher levels of travel; shoplifting is lower when there is a reduced rail service. There was no clear relationship between shoplifting rates outside of a station at shops nearby, and shoplifting within a rail station. It is suggested a correlation may occur for medium and smaller size stations. Large stations may attract offenders in their own right without other shops being nearby. The similarities observed between shoplifting patterns at rail stations and those at non-rail station shops suggest the learning from successful crime prevention measures applied outside of the rail environment could successfully transferred to rail stations

Theoretical perspectives of safety and security in transit environments

This chapter discusses the extant theories used to explain safety and security in transit environments, which are set out within the conceptual framework identified in the previous chapter. A number of theoretical perspectives have been developed to explain the prevalence of crime, disorder and associated fear in society. None of these are without criticism, and none have been developed explicitly for the purpose of explaining safety and security on public transport systems. This section examines current security and criminological theories, and ideas and perspectives from other fields and disciplines, to ascertain their utility for explaining safety and security specifically in the context of public transportation. The aim is to translate these theories into an integrated and theory-led conceptual framework within which safety and security on public transport systems can readily be examined

Myrmekite and strain weakening in granitoid mylonites

At mid-crustal conditions, deformation of feldspar is mainly accommodated by a combination of fracturing, dissolution\u2013precipitation, and reaction-weakening mechanisms. In particular, K-feldspar is reaction-weakened by the formation of strain-induced myrmekite \u2013 a \ufb01ne-grained symplectite of plagioclase and quartz. Here we use electron backscattered diffraction to (i) investigate the microstructure of a granodiorite mylonite, developed at 3c 450 \ub0C during cooling of the Rieserferner pluton (Eastern Alps); and (ii) assess the microstructural processes and the weakening associated with myrmekite development. Our analysis shows that the crystallographic orientation of plagioclase in pristine myrmekite was controlled by that of the replaced K- feldspar. Myrmekite nucleation resulted in both grain-size reduction and anti-clustered phase mixing by heterogeneous nucleation of quartz and plagioclase. The \ufb01ne grain size of sheared myrmekite promoted grain-size-sensitive creep mechanisms including \ufb02uid-assisted grain boundary sliding in plagioclase, coupled with heterogeneous nucleation of quartz within creep cavitation pores. Flow laws, calculated for monomineralic quartz, feldspar, and quartz + plagioclase aggregates (sheared myrmekite) during deformation at 450 \ub0C, show that grain-size-sensitive creep in sheared myrmekite accommodated strain rates several orders of magnitude higher than monomineralic quartz layers deforming by dislocation creep. Therefore, diffusion creep and grain size-sensitive processes contributed signi\ufb01cantly to bulk rock weakening during mylonitization. Our results have implications for modelling the rheology of the felsic middle crust