Videogame localization. A case study: Final Fantasy XII

Globalization has influenced all economic sectors and the demand for translation services has increased like never before. The videogame industry has become a worldwide phenomenon worth billions. Many people around the globe, male and female, children and adults alike, choose this leisure activity and enjoy it like reading or watching a film. It is a global phenomenon capable of producing as much revenue and anticipation as the film industry. Most games are developed in Japanese or English and the new global market requires this product to be translated into many other languages. The scenario has brought about a new field of specialization in translation studies, commonly known as videogame localization. The emergence of this new field calls not only for a review of translation studies, but also a shift in the role that some translators and translated products are expected to play within a globalized world. The aim of this dissertation is to provide an overview of videogame localization and its challenges under the guidance of a professional translator such as Alexander O. Smith, who agreed to provide counsel through several Skype interviews. This provided a first-hand insight into how translation decisions are carried out by game translators. Alexander O. Smith was a former translator for Square Enix, one of the biggest Japanese videogame developer, publisher and distribution company in the market. He now works as an independent translator and in 2003 he founded the localization agency called Kajiya Productions with his friend and fellow translator Joseph Reeder. Together with Alexander O. Smith, the twelfth installment of the Final Fantasy series by Square Enix has been chosen as a very good example of the issues and challenges brought on by videogame localization. The game which revealed itself to be one of the most fun, challenging and rewarding professional experiences of Alexander O. Smith.

Geometric versus Model Predictive Control based guidance algorithms for fixed-wing UAVs in the presence of very strong wind fields.

The recent years have witnessed increased development of small, autonomous fixed-wing Unmanned Aerial Vehicles (UAVs). In order to unlock widespread applicability of these platforms, they need to be capable of operating under a variety of environmental conditions. Due to their small size, low weight, and low speeds, they require the capability of coping with wind speeds that are approaching or even faster than the nominal airspeed. In this thesis, a nonlinear-geometric guidance strategy is presented, addressing this problem. More broadly, a methodology is proposed for the high-level control of non-holonomic unicycle-like vehicles in the presence of strong flowfields (e.g. winds, underwater currents) which may outreach the maximum vehicle speed. The proposed strategy guarantees convergence to a safe and stable vehicle configuration with respect to the flowfield, while preserving some tracking performance with respect to the target path. As an alternative approach, an algorithm based on Model Predictive Control (MPC) is developed, and a comparison between advantages and disadvantages of both approaches is drawn. Evaluations in simulations and a challenging real-world flight experiment in very windy conditions confirm the feasibility of the proposed guidance approach.

Design and management of a supply chain: a joint location-inventory problem under uncertainty (Part A)

In this paper, a joint location-inventory model is proposed that simultaneously optimises strategic supply chain design decisions such as facility location and customer allocation to facilities, and tactical-operational inventory management and production scheduling decisions. All this is analysed in a context of demand uncertainty and supply uncertainty. While demand uncertainty stems from potential fluctuations in customer demands over time, supply-side uncertainty is associated with the risk of “disruption” to which facilities may be subject. The latter is caused by external factors such as natural disasters, strikes, changes of ownership and information technology security incidents. The proposed model is formulated as a non-linear mixed integer programming problem to minimise the expected total cost, which includes four basic cost items: the fixed cost of locating facilities at candidate sites, the cost of transport from facilities to customers, the cost of working inventory, and the cost of safety stock. Next, since the optimisation problem is very complex and the number of evaluable instances is very low, a "matheuristic" solution is presented. This approach has a twofold objective: on the one hand, it considers a larger number of facilities and customers within the network in order to reproduce a supply chain configuration that more closely reflects a real-world context; on the other hand, it serves to generate a starting solution and perform a series of iterations to try to improve it. Thanks to this algorithm, it was possible to obtain a solution characterised by a lower total system cost than that observed for the initial solution. The study concludes with some reflections and the description of possible future insights.