With the number of vehicles increasing in the system every day, many statewide policies across the United States aim to increase the use of non- motorized transportation modes. This could have safety implications because the interaction between motorists and non-motorists could increase and potentially increasing pedestrian-vehicle crashes. Few models that predict the number of pedestrian crashes are not sensitive to site-specific conditions or intersection designs that may influence pedestrian crashes. Moreover, traditional statistical modeling techniques rely extensively on the sparsely available pedestrian crash database. This study focused on overcoming these limitations by developing models that quantify potential interactions between pedestrians and vehicles at various intersection designs using as surrogate safety measure the time to conflict. Several variables that capture volumes, intersection geometry, and operational performance were evaluated for developing pedestrian-vehicle conflict models for different intersection designs. Linear regression models were found to be best fit and potential conflict models were developed for signalized, unsignalized and roundabout intersections. Volume transformations were applied to signalized and unsignalized conditions to develop statistical models for unconventional intersections. The pedestrian-vehicle conflicting volumes, the number of lanes that pedestrians are exposed to vehicles, the percentage of turning vehicles, and the intersection conflict location (major or minor approach) were found to be significant predictors for estimating pedestrian safety at signalized and unsignalized intersections. For roundabouts, the pedestrian-vehicle conflicting volumes, the number of lanes that pedestrians have to cross, and the intersection conflict location (major or minor approach) were found to be significant predictors. Signalized intersection models were used for bowtie and median U-turn intersections using appropriate volume transformations. The combination of signalized intersection models for the intersection area and two-way unsignalized intersection models for the ramp area of the jughandle intersections were utilized with appropriate volume transformations. These models can be used to compare alternative intersection designs and provide designers and planners with a surrogate measure of pedestrian safety level for each intersection design examined.

Recent conflict research has relied on proxy variables of horizontal inequality to make causal assumptions, but these do not reveal the root of deprivation in aggrieved populations. However, it is important to continue to explore the greed-grievance dichotomy to explain the persistence of violent civil conflict. The purpose of this quantitative study was to expand this line of inquiry by investigating the relationship between indicators of vertical deprivation and reported civil conflict incidents to determine whether a significant correlation exists. Relative deprivation theory provided the framework for this study, which consisted of 10,779 survey responses regarding lived experience across 7 countries experiencing a total of 890 civil conflict incidents in 2016. Although tests of multiple linear regression indicated statistically significant relationships (p < .001) between two of the predictor variables and reported civil conflict incidents, the availability of electricity when connected to the main made the most substantial contribution to the model in both predictability and correlation. Therefore, the findings provide insight into the type and nature of deprivations, such as those associated with access to and availability of electricity, that have the greatest potential of becoming grievances susceptible to exploitation by conflict entrepreneurs. Implications for positive social change include using this analysis to promote increased conflict inquiry among public administration scholars and to inform a more substantive role of local government managers in identifying and remediating vertical grievances, thereby mitigating civil conflict.

This diploma thesis deals with the topic of Early Warning Systems (EWS), a key part of conflict prevention. It applies a model of quantitative analysis of international media outputs on the case of the Mali insurgency in January 2012. As an EWS tool, it analyzes international media represented by the major global press agencies. The main goal of the thesis is to answer the following research question: Did the international media manage to anticipate the outbreak of the conflict in Mali? The answer should also show whether international media can detect growing tensions leading to a conflict and therefore whether they could be used as an EWS tool. The application of the model should, observing the period from August 2011 to the beginning of the insurgency on January 17, 2012, prove whether the conflict could have been anticipated. In order to contextualize the model, structural factors of instability were identified in the discussion of the dynamics of the conflict that has been repeating itself for dozens of years. A discourse analysis of international media during the observed period was also presented on the background of the securitization theory of the Copenhagen school of security studies. The discourse analysis and the quantitative EWS model have both shown that international media have not...

Our project, ViEWS+, expands the software functionality of the Violence EarlyWarning System (ViEWS). ViEWS aims to predict the probabilities of armed conflicts in the next 36 months using machine learning. Governments and policy-makers may use conflict predictions to decide where to deliver aid and resources, potentially saving lives. The predictions use conflict data gathered by ViEWS, which includes variables like past conflicts, child mortality and urban density. The large number of variables raises the need for a selection tool to remove those that are irrelevant for conflict prediction. Before our work, the stakeholders used their experience and some guesswork to pick the variables, and the predictive function with its parameters. Our goals were to improve the efficiency, in terms of speed, and correctness of the ViEWS predictions. Three steps were taken. Firstly, we made an automatic variable selection tool. This helps researchers use fewer, more relevant variables, to save time and resources. Secondly, we compared prediction functions, and identified the best for the purpose of predicting conflict. Lastly, we tested how parameter values affect the performance of the chosen functions, so as to produce good predictions but also reduce the execution time. The new tools improved both the execution time and the predictive correctness of the system compared to the results obtained prior to our project. It is now nine times faster than before, and its correctness has improved by a factor of three. We believe our work leads to more accurate conflict predictions, and as ViEWS has strong connections to the European Union, we hope that decision makers can benefit from it when trying to prevent conflicts. / I detta projekt, vilket vi valt att benämna ViEWS+, har vi förbättrat olika aspekter av ViEWS (Violence Early-Warning System), ett system som med maskinlärning försöker förutsäga var i världen väpnade konflikter kommer uppstå. Målet med ViEWS är att kunna förutsäga sannolikheten för konflikter så långt som 36 månader i framtiden. Målet med att förutsäga sannoliketen för konflikter är att politiker och beslutsfattare ska kunna använda dessa kunskaper för att förhindra dem.  Indata till systemet är konfliktdata med ett stort antal egenskaper, så som tidigare konflikter, barnadödlighet och urbanisering. Dessa är av varierande användbarhet, vilket skapar ett behov för att sålla ut de som inte är användbara för att förutsäga framtida konflikter. Innan vårt projekt har forskarna som använder ViEWS valt ut egenskaper för hand, vilket blir allt svårare i och med att fler introduceras. Forskargruppen hade även ingen formell metodik för att välja parametervärden till de maskinlärningsfunktioner de använder. De valde parametrar baserat på erfarenhet och känsla, något som kan leda till onödigt långa exekveringstider och eventuellt sämre resultat beroende på funktionen som används. Våra mål med projektet var att förbättra systemets produktivitet, i termer av exekveringstid och säkerheten i förutsägelserna. För att uppnå detta utvecklade vi analysverktyg för att försöka lösa de existerande problemen. Vi har utvecklat ett verktyg för att välja ut färre, mer användbara, egenskaper från datasamlingen. Detta gör att egenskaper som inte tillför någon viktig information kan sorteras bort vilket sparar exekveringstid. Vi har även jämfört prestandan hos olika maskinlärningsfunktioner, för att identifiera de bäst lämpade för konfliktprediktion. Slutligen har vi implementerat ett verktyg för att analysera hur resultaten från funktionerna varierar efter valet av parametrar. Detta gör att man systematiskt kan bestämma vilka parametervärden som bör väljas för att garantera bra resultat samtidigt som exekveringstid hålls nere. Våra resultat visar att med våra förbättringar sänkes exekveringstiden med en faktor av omkring nio och förutsägelseförmågorna höjdes med en faktor av tre. Vi hoppas att vårt arbete kan leda till säkrare föutsägelser och vilket i sin tur kanske leder till en fredligare värld.

Inadequate economic data makes it more difficult for its incorporation in security-policy related prediction and there is a need for alternative datasets. Satellite data, more specifically nighttime lights data, can be used as a proxy for the economy. In this project, the correlation between nighttime lights and the economy between 1992 and 2018 is explored for five countries in Africa: Nigeria, Libya, the Central African Republic, the Republic of the Congo and Ghana. Data from two different satellite series, DMSP-OLS and VIIRS-DNB are used, and the extracted datasets are calibrated for the differences or intercalibrated. There was found to be a high correlation for two of the countries, the Republic of the Congo and Ghana. The biggest improvement can be made by developing the intercalibration method. A pitfall of the method is that it is not generally applicable as unique circumstances seen for Nigeria show in the correlation results.