The postsecondary acts of violence at Virginia Technical University (VT) and Northern Illinois University (NIU) forced Illinois legislators to approve the Campus Security Enhancement Act in 2008 (110 ILCS 12/20). The Act requires all private and public postsecondary education institutions to develop a Campus Violence Prevention Plan (CVPP), as well as two multi-disciplinary groups to implement the plan and address behaviors of concern, a Campus Violence Prevention Committee (CVPC) and Threat Assessment Team (TAT) (CESA, 2008). Recent research has uncovered that several institutions within the state have not completed their CVPP and the Act has left some institutions unsure of which agency to report to and how to effectively develop and implement their CVPP (Gregory, 2012; Pawlowski & Manetti, 2011). This research study is the first investigation into the groundbreaking Illinois legislation. Utilizing a case study design, the purpose of the research study is to explore how three Illinois postsecondary institutions of similar Carnegie classifications created, implemented, assessed, and addressed challenges in developing their CVPP's. One-on-one interviews and document analysis were used to gather data. With-in case analysis and cross-case analysis were performed to generated research themes to answer the research questions. Four cross-case analysis themes were created to answer the corresponding research questions. Conclusions from this study may assist other Illinois postsecondary institutions in developing their CVPP's and decrease the likelihood of violence occurring in the postsecondary environment.

The Grassland biome of South Africa has been identified as critically endangered and the biome in South Africa most requiring conservation attention through the implementation of efficient, sustainable systematic conservation plans. The ability to predict where land-cover transformation as well as information on the occurrence and severity of current land cover transformation activities, as threats to biodiversity, is required as part of the systematic conservation planning process. Neke & du Plessis (2004) predicted land cover transformation and the severity of the impact on biodiversity in the Grassland biome. This model was based on potential land use suitability models and land cover information for the 1994/5 season extracted from the National Land Cover database (NLC1994). These predictions were tested by assessing actual land cover change in the Grassland biome using observed differences in grassland land cover between the NLC1994 and NLC2000 databases. Methodology Because of differences in format and land-cover classification between the original datasets, both NLC1994 and NLC2000 had to be modified before any analyses could be carried out. These differences exist because different techniques were used to collate the respective datasets, thus introducing the potential for significant mapping error in the original datasets and more significantly erroneous results with respect to landcover change detection. The implications of this were presented in the discussion. Both datasets were spatially resampled and class-standardised and it was felt that this would significantly reduce any the impact of any such existing errords in the original datasets. Thereafter landcover information for the Grassland biome was be extracted and the comparative landcover analyses executed. The analyses carried out included: • Landcover change per landcover class within the Grassland biome with emphasis on the Grassland landclass losses and gains • An assessment and comparison of the relative fragmentation of the remaining grassland patches in both datasets • An assessment of current grassland habitat degradation • The comparison of the predicted land cover change as given by Neke & du Plessis (2004) against the observed grassland changes • The creation of a new Grassland Transformation threat map reflecting current land cover change threats, and including information pertaining to the threats to Grassland biodiversity posed by invasive alien plants, road effects, urban areas and soil erosion hazards. Results and Discussion 25% of the remaining grassland patches underwent transformation to other land classes. Grassland clearing for cultivation, bush encroachment and bushland vegetation regeneration were the main causal factors behind the observed grassland losses. However, grassland vegetation regeneration on formerly cultivated land, bush clearing and reclassification of degraded lands as grasslands in the NLC2000 dataset contributed to a net 2% gain in area of the grassland land class. The remaining grassland patches are more fragmented than they were in NLC1994, the average patch size (NLC2000) is three times smaller and the total number of grassland patches has increased (also by a factor of 3) and the remaining grassland patches are more isolated. The largest, least fragmented grassland patches occur along and to the west of the Great Escarpment as it traverses the Grassland biome. Most of the predictions of grassland transformation were realised, however the model used by Neke & du Plessis (2004) consistently underestimated and in some cases failed to predict the occurrence of grassland transformation in the central interior of the Grassland biome. Current, measurable human activities that act as grassland transformation agents were incorporated to create a threat map showing the extent and severity of land-cover transformation activities within the biome; grassland bird species richness information was then incorporated into this map to create biodiversity transformation threat map. This map was used to show the location and severity of the impacts of human transformation activities on grassland biodiversity. Both transformation threat map reflect the current situation across the biome today and were compared against the Potential transformation threat map produced by Neke & du Plessis (2004). The human transformation threat map confirmed the inability of the Neke & du Plessis model to make correct predictions of land cover change away from the eastern, 7 high altitude boundary of the biome. Given that the biome is defined by its climatic characteristics, the incorporation of global climate change effects would further refine the results gained, and perhaps provide more accurate predictions. As aforementioned, there are however factors existing within the original datasets used in this analysis that may have affected the accuracy of the landcover change analyses. These factors are centred on the potential effects of mapping errors within either of the NLC datasets. The delineation of landclass boundaries in the NLC1994 dataset is one such factor- placing a line over what is in reality a gradient of changing vegetation, is a subjective exercise and depends entirely on the technician involved this in itself may have introduced a fair amount of error in the mapping process. When coupled with the automated classification techniques used, for the most part, for the NLC2000 dataset, it becomes apparent that it is highly unlikely that even in the absence of actual landcover change the same boundaries would be drawn between two landclasses in the same area. This would provide false positive results for landcover change where in fact this is as a result of mapping errors. This is acknowledged and included in the interpretation of the results and it is felt that in spite of this, all possible steps were taken to minimize the impact of these effects on the reslults. The analysis allowed the identification of the current land cover transformations leading to grassland loss. However, land-cover change is only the physical expression of the complex interactions between socio-economic factors. To create effective and sustainable conservation plan for the Grassland biome, with an aim to reducing habitat loss requires an action plan to address these factors as the ultimate drivers of land cover change.

My aim is to design a research program that emphasizes inclusivity through empiricism rather than anecdotes and benevolent sexism. To accomplish this goal, I review and build on the work assessing the influence of fertility in the female consumer experience (FCE). Fertility, especially menstruation, has been used anecdotally for too long. This research was designed to address the gap in knowledge around the way in which women perceive advertisements. More specifically, the role fertility plays in the process women go through when assessing advertisements and offerings. Does a woman's desire to seek variety become reduced when she sees a rival endorsing the offering? If this is the case, then there is a need to find a mediating variable that can overcome this effect. Internal locus of control, the level a person feels they are in control of the outcomes in their lives, was selected as a starting point. Having a high internal LOC should buffer a person's perceptions of another as a threat. A cross-sectional design from a convenience sample of university students was used to address a series of five research questions: 1) Does fertility status influence locus of control, 2) Does fertility status influence rival assessment, 3) Does locus of control mediate rival assessment, 4) Does rival assessment influence advertisement assessment and purchase intent, and 5) Does external locus of control have more than a single factor? The results from the multiple one-way ANOVAs and linear regressions were not significant, but it was promising given the limitations of the study. Namely, the rate of unusable data combined with the rate of birth control use limited the final analyses to a sample of 62 cases. Additional considerations and future research directions are outlined in chapter 5.

This study focuses on how important foreign policy crises are interpreted and used to construct images and framing of transnational threats. Since Russia’s annexation of Crimea, Ukraine 2014, the security order in Europe and within the European Union has been affected in various ways because of how Russia is portrayed as a potential threat. Accordingly, the aim of the study is the examination of the extent of EU’s framing of Russia as a military and political threat in the annual Common Foreign and Security Policy (CFSP) reports between 2012-2020. Through a qualitative content analysis with a quantitative conception, the aim is to identify the negative frames of demonization that can be distinguished in the CFSP reports that correlate to EU’s framing of Russia as a threat. The theories of neoclassical realism, demonization and framing are used to provide the deductive approach of indicators that construct the frames of categorization for Russia as a military and political threat within the CFSP reports. The study concludes that the EU has framed Russia as a military threat in relation to Russia’s border transgression within Ukraine, implementing the annexation of Crimea, and Georgia. Russia is also demonized as a political threat through means that intend to cause instability in neighboring states in order to influence domestic policies, for example economic-induced pressures, spread of disinformation, and different kinds of hybrid weapons.

This thesis is a comparative study of the national security strategies of Sweden, Russia and the Czech Republic. The analysis investigates the contextual analysis made by each country and the identified security threats. To compare and find out the similarities and differences two theoretical approaches are used: realism and liberalism. To compare and identify the threats a five factor model is used, originating of general military threat assessment. / <p>Erasmus</p>

Cybersecurity threats have surged in the past decades. Experts agree that conventional security measures will soon not be enough to stop the propagation of more sophisticated and harmful cyberattacks. Recently, there has been a growing interest in mastering the complexity of cybersecurity by adopting methods borrowed from Artificial Intelligence (AI) in order to support automation. Moreover, entire security frameworks, such as DETECT (Decision Triggering Event Composer and Tracker), are designed aimed to the automatic and early detection of threats against systems, by using model analysis and recognising sequences of events and other tropes, inherent to attack patterns. In this project, I concentrate on cybersecurity threat assessment by the translation of Attack Trees (AT) into probabilistic detection models based on Bayesian Networks (BN). I also show how these models can be integrated and dynamically updated as a detection engine in the existing DETECT framework for automated threat detection, hence enabling both offline and online threat assessment. Integration in DETECT is important to allow real-time model execution and evaluation for quantitative threat assessment. Finally, I apply my methodology to some real-world case studies, evaluate models with sample data, perform data sensitivity analyses, then present and discuss the results.

<p>This thesis presents improvements and extensions of a previously presented threat assessment algorithm. The algorithm uses Monte Carlo simulation to find threats in a road scene. It is shown that, by using a wider sample distribution and only apply the most likely samples from the Monte Carlo simulation, for the threat assessment, improved results are obtained. By using this method more realistic paths will be chosen by the simulated vehicles and more complex traffic situations will be adequately handled.</p><p>An improvement of the dynamic model is also suggested, which improves the realism of the Monte Carlo simulations. Using the new dynamic model less false positive and more valid threats are detected.</p><p>A systematic method to choose parameters in a stochastic space, using optimisation, is suggested. More realistic trajectories can be chosen, by applying this method on the parameters that represents the human behaviour, in the threat assessment algorithm.</p><p>A new definition of obstacles in a road scene is suggested, dividing them into two groups, Hard and Soft obstacles. A change to the resampling step, in the Monte Carlo simulation, using the soft and hard obstacles is also suggested.</p>

Visualising uncertainty information has been a research area for the past decade or so, and this thesis contains the results of an experiment that examines whether prior research on icon degradation for showing uncertainty can be used in a simulated aircraft cockpit environment. Using icon degradation has been suggested as being effective to combat overconfidence bias, as well as to accurately convey information about uncertainty. Two icon sets using icon degradation were taken from prior research, and one new icon set using shape change and colour change was created for comparison. Subjects flew a flight simulator while reading icons to evaluate the uncertainty displayed, and also evaluating their own confidence in their reading. The results show that shape change leads to much higher accuracy in reading icons, and slightly higher levels of confidence. Furthermore, icon degradation results in a higher variance in reading icons and an increase in errors when no time-pressure or distraction is present. This suggests that the suitability of icon degradation for showing uncertainty is questionable in all situations, and that other design approaches such as shape change should be considered. Furthermore, problems were uncovered in the prior research that the old icons were taken from, and these problems call into question the general approach used in that research. Keywords: Uncertainty visualisation, Naturalistic decision-making, NDM, Aviation, Aircraft cockpit, Decision support, Situation assessment, Threat assessment.

This thesis presents improvements and extensions of a previously presented threat assessment algorithm. The algorithm uses Monte Carlo simulation to find threats in a road scene. It is shown that, by using a wider sample distribution and only apply the most likely samples from the Monte Carlo simulation, for the threat assessment, improved results are obtained. By using this method more realistic paths will be chosen by the simulated vehicles and more complex traffic situations will be adequately handled. An improvement of the dynamic model is also suggested, which improves the realism of the Monte Carlo simulations. Using the new dynamic model less false positive and more valid threats are detected. A systematic method to choose parameters in a stochastic space, using optimisation, is suggested. More realistic trajectories can be chosen, by applying this method on the parameters that represents the human behaviour, in the threat assessment algorithm. A new definition of obstacles in a road scene is suggested, dividing them into two groups, Hard and Soft obstacles. A change to the resampling step, in the Monte Carlo simulation, using the soft and hard obstacles is also suggested.

Stalking - criminological aspects Abstract The issue of this thesis is the criminological aspects of the crime of stalking in Czech Republic according to section 354 of the Act no. 40/2009 Coll., Criminal Code. The thesis consists of three parts. The first part is focused on the characteristics of the concept of stalking, its criminalization and analysis of the crime of stalking from the point of view of substantive and procedural criminal law. The second part contains knowledge about the personality of stalking perpetrators, several selected typologies of perpetrators and practical advice and recommendations in connection with helping victims of stalking. The last part deals with the threat assessment which stalking perpetrators pose to their victims. Furthermore, it is the focus of the thesis, which is the analysis of the concept of "reasonable concern" in the context of the crime of stalking. The last chapter of this part is devoted to the analysis of 4 cases of stalking from a criminological point of view. The conclusion of the thesis consists of a summary of the most important findings that the author found during her writing. Keywords: stalking/ reasonable concern / threat assessment