Can France really stop them? : A study grounded on the realist perspective about the French foreign policy towards Syria as the root cause of the Phenomenon of French Foreign Fighters

During the Syrian conflict the number of European Foreign Fighters has increased exponentially and has become an ever-growing concern for European policymakers. This phenomenon presents host of major security challenges for European policymakers and governments. Among European countries, France provides the highest number of citizens who have gone to Syria to fight against Assad´s regime. The French authorities have estimated that by mid-2014, over 700 French citizens have left France and travelled to Syria to fight. Historically France has had a relationship with Syria which started with its role as a border-drawing colonial power. Grounded in a framework of realism, that emphasizes nation-states as the primary actor within the international system, the analysis concentrates on the role of France´s foreign policy on the Syria as push factor for terrorism and radicalization. This paper attempts to determinate a specific correlation between the policy that France has been conducting towards Syria between 2000 and 2015, and the phenomenon of French Foreign Fighters. Findings suggest that France´s foreign policy towards Syria is the main root cause of the French Foreign Fighters phenomenon.

Triggering Solar-Powered Vehicle Activated Signs using Self Organising Maps with K-means

Solar-powered vehicle activated signs (VAS) are speed warning signs powered by batteries that are recharged by solar panels. These signs are more desirable than other active warning signs due to the low cost of installation and the minimal maintenance requirements. However, one problem that can affect a solar-powered VAS is the limited power capacity available to keep the sign operational. In order to be able to operate the sign more efficiently, it is proposed that the sign be appropriately triggered by taking into account the prevalent conditions. Triggering the sign depends on many factors such as the prevailing speed limit, road geometry, traffic behaviour, the weather and the number of hours of daylight. The main goal of this paper is therefore to develop an intelligent algorithm that would help optimize the trigger point to achieve the best compromise between speed reduction and power consumption. Data have been systematically collected whereby vehicle speed data were gathered whilst varying the value of the trigger speed threshold. A two stage algorithm is then utilized to extract the trigger speed value. Initially the algorithm employs a Self-Organising Map (SOM), to effectively visualize and explore the properties of the data that is then clustered in the second stage using K-means clustering method. Preliminary results achieved in the study indicate that using a SOM in conjunction with K-means method is found to perform well as opposed to direct clustering of the data by K-means alone. Using a SOM in the current case helped the algorithm determine the number of clusters in the data set, which is a frequent problem in data clustering.