El presente trabajo universitario desarrollado por Jorge Tulio Pickmans León, en calidad de estudiante de la facultad de Comunicaciones en la especialidad de Audiovisual y Medios Interactivos, de la Universidad Peruana de Ciencias Aplicadas, tiene como finalidad ser un trabajo de investigación con tema principal el desarrollo de videojuegos en el Perú, precisamente de Lima provincia, y cómo estos son vistos en un entorno internacional. Además de analizar los factores de desarrollo que están impulsando o retrasando esta joven industria. Para ello, se investigará el mercado y el público objetivo a través de un estudio mixto de investigación. Y con ello, analizar las principales empresas del rubro: Bamtang Games y Leap Game Studios, y sus aportes en el mercado. / The present university work written by Jorge Tulio Pickmans León, as a student of the Communication faculty in the specialty of Audiovisual and Interactive Media, of the “Universidad Peruana de Ciencias Aplicadas” (Peruvian University of Applied Sciences), aims to be an investigation project having as a main topic the development of video games in Peru, precisely from Lima City, and how they are seen in an international environment. Plus, to analyze the development factors that are improving or delaying this young industry. In order to do this, the market and the target audience will be investigated through a mixes research study. And with that, analyze the main companies in the work field: Bamtang Games and Leap Game Studios, and their contributions in the market. / Trabajo de investigación

This thesis focuses on the development and analysis of efficient simulation and inference techniques for Markovian pure jump processes with a view towards applications in dense communication networks. These techniques are especially relevant for modeling networks of smart devices —tiny, abundant microprocessors with integrated sensors and wireless communication abilities— that form highly complex and diverse communication networks. During 2010, the number of devices connected to the Internet exceeded the number of people on Earth: over 12.5 billion devices. By 2015, Cisco’s Internet Business Solutions Group predicts that this number will exceed 25 billion. The first part of this work proposes novel numerical methods to estimate, in an efficient and accurate way, observables from realizations of Markovian jump processes. In particular, hybrid Monte Carlo type methods are developed that combine the exact and approximate simulation algorithms to exploit their respective advantages. These methods are tailored to keep a global computational error below a prescribed global error tolerance and within a given statistical confidence level. Indeed, the computational work of these methods is similar to the one of an exact method, but with a smaller constant. Finally, the methods are extended to systems with a disparity of time scales. The second part develops novel inference methods to estimate the parameters of Markovian pure jump process. First, an indirect inference approach is presented, which is based on upscaled representations and does not require sampling. This method is simpler than dealing directly with the likelihood of the process, which, in general, cannot be expressed in closed form and whose maximization requires computationally intensive sampling techniques. Second, a forward-reverse Monte Carlo Expectation-Maximization algorithm is provided to approximate a local maximum or saddle point of the likelihood function of the parameters given a set of observations. The third part is devoted to applications in communication networks where also mean field or fluid approximations techniques, to substantially reduce the computational work of simulating large communication networks are explored. These methods aim to capture the global behaviour of systems with large state spaces by using an aggregate approximation, which is often described by means of a non-linear dynamical system.

The thesis deals with the design and implementation of user interface for robotic manipulator control by means of gesture detection of the operator. The used manipulator is the Katana 6M180 with five degrees of freedom. Gestures are detected using an innovated sensor system which includes Microsoft Kinect version 2 and Leap Motion sensors. The first part provides an overview of existing solutions and used technologies. The second part describes the design of the user interface, its implementation and testing.

Several studies have been conducted and revealed that household is the major energy consumer sector in developing countries like Ethiopia. This study focuses on evaluation of the existing residential energy consumption and projection of the energy demand.   The energy consumption has been studied by conducting survey on 350 households using stratified random sampling technique. Then the analyzed data have been used to model the energy demand and to project the future energy consumption till 2030 using LEAP (Long Range Energy Alternative Planning) simulation software.   The model is done based upon baseline scenario and energy efficiency improvement scenario (mitigation scenario). The total energy consumption in Bahir dar in 2014 is nearly 330 Giga watt hour per year, and of this value about 83.8% is used for cooking and TV, lighting, refrigerator, and water heater consume 7%, 4.5%, 3.5%, 1%  of the total energy and remaining 0.2% is consumed for other auxiliary appliances. The projection of the energy consumption in 2030 will be more 450 Giga-watt-hour with business as usual scenario compared to just less than 350 Giga-watt-hour with mitigation scenario. As the result of the poor consumption efficiency, households that use traditional biomass tend to have more primary energy intensity than household that use electricity. The consumption of electricity is projecting rapidly while charcoal and firewood will still be the significant energy sources. The potential for energy saving is from improving the efficiency of stoves. Comparing with developed countries, for example Sweden, where the energy in dwellings is mostly used for space and water heating and the energy saving mostly target on improving wall insulations, the energy saving on Bahir dar is based mostly on cooking. The findings obtained in this shows options to improve household energy efficiency intervention planning and to enhance the effectiveness of policy interventions. Further studies could be done on modeling of other sectors.

Kenya is at the forefront of a socioeconomic transformation, aiming to turn into an industrialized middle income country by 2030. Kenya Vision 2030 has identified energy as a key foundation and one of the infrastructural “enablers” upon which the economic, social and political pillars of this long-term development strategy will be built. Predicting the future of energy systems however, involves risks due to various uncertainties. Therefore, systematic energy planning at national and sub-national/County level is highly recommended through the adoption of more realistic assumptions on the future evolution and profile of demand and robust pre-feasibility of prospective projects including the integration of renewable energy sources, which the country is endowed with. This thesis provides a comprehensive analysis of the energy sector for Kakamega County in Western Kenya. The current energy demand level was estimated for six selected sectors of the County namely Residential, Industrial, Transportation, Commercial, Public and Agricultural. Additionally, the renewable energy resources potential was assessed at local level using GIS and other available data. LEAP software was used in order to model and project the energy demand and supply based on three 15-year scenarios till 2030, developed to support the economic, social and environmental sustainability of the County. This study intended to create a framework aiming to facilitate sub-national energy planning in developing countries and it is expected that the findings will be complementary to already existing energy planning models but also the base for future research towards energy poverty elimination.

It is estimated that transport sources in developing countries contribute about 4% of the global fossil carbon dioxide versus 18% by industrialized countries. The cost of urban air pollution is estimated to be 2% of GDP in developed countries and more than 5% in developing countries. With an annual vehicle registration growth of over 30% in 2008 and a population growth rate of 6%, the number of automobiles in Kampala city of Uganda is expected to continue growing exponentially. Most of the vehicles used are imported into the country when quite old with worn out engines and low energy efficiencies. As a result, such vehicles profusely emit exhaust gases which may be harmful to both human health and the environment. Controlling pollution from the transport sector is vital to improving the quality of air and protecting public health. The objective of this dissertation was to determine the level of pollution from automobile exhaust gases in Kampala City and its impacts on human health and the environment. The study involved the analysis of tail pipe emissions using a gas analyser. It covered mini buses, motorcycles and personal vehicles which constitute 92% of the Kampala vehicle parc. It was established that the main types of exhaust gases from the automobiles were CO2,  NOx, CO, NO and HC. The findings estimated the highest level of NOx tail pipe emissions at 0.15 mg/m3, HC emissions at 2.59 mg/m3, CO at 110 mg/m3 and 286.6 mg/m3 for CO2. The reported ambient air emissions were estimated at 0.18 ppm, 14000 ppm and 1.3 ppm corresponding to NO2, CO2 and CO, respectively. The study further investigated the impact of four mitigation methods on emission levels using the LEAP model. The impact of increasing penetration of city buses, introduction of tail pipe emission standards and hybrid cars and improvement of vehicle fuel economy were investigated. It was found that if left unabated, the emissions will continue to grow with the increasing number of motor vehicles. Implementation of the proposed mitigation methods resulted in a reduction in the GWP reduced by 52%, 51%, 17% and 8.5%, respectively. It is recommended that a comprehensive motor vehicle pollution control program be designed to implement the proposed NEMA vehicle emission standards. Establishment of an integrated transport system promoting the growth in number of city buses should be made a priority to reduce on emission levels and enable the decongestion of Kampala city.

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Chronic pain (CP) significantly affects participation in meaningful occupations. It is a public health problem that comes with substantial social and economic costs (Dagenais et al., 2008; Dahlhamer et al., 2018; Geurts et al., 2018; Treede et al., 2015; Willems et al., 2018). Creating a successful intervention for CP is challenging due to the subjectivity of the pain experience and the complexity of factors associated with pain behavior (Newton et al., 2013; Polacek et al., 2020; Van Huet et al., 2012). This doctoral project details the development of the Sustained-pain Treatment through Augmented Reality Occupation-based Protocol (STAR-OP), a novel treatment protocol that offers practical solutions for an outpatient occupation-based CP intervention. The STAR-OP addresses critical issues for the CP population, including expectation management, home assignments adherence, and the generalization process from clinical practice to the client's home environment. The STAR-OP program uses Augmented Reality technology to facilitate a gradual generalization process, Motivational Interviewing techniques to enhance the therapeutic relationship's effectiveness, and the educational content of the Lifestyle Redesign® protocols presented through an occupational perspective (A. Simon & Collins 2017). The STAR-OP program evaluation examines the effectiveness of the STAR-OP, via a multiple-baseline, single-subject design, institutional review board (IRB)-approved study to be conducted at Lowenstein Rehabilitation Center in Israel.

The Finite Element Tearing and Interconnecting (FETI) and its variants are probably the most celebrated domain decomposition algorithms for partial differential equation (PDE) scientific computations. In electromagnetics, such methods have advanced research frontiers by enabling the full-wave analysis and design of finite phased array antennas, metamaterials, and other multiscale structures. Recently, closer scrutiny of these methods have revealed robustness and numerical scalability problems that prevent the most memory and time efficient variants of FETI from gaining widespread acceptance. This work introduces a new class of FETI methods and preconditioners that lead to exponential iterative convergence for a wide class of problems, are robust and numerically scalable. First, a two Lagrange multiplier (LM) variant of FETI with impedance transmission conditions, the FETI-2λ, is introduced to facilitate the symmetric treatment of non-conforming grids while avoiding matrix singularites that occur at the interior resonance frequencies of the domains. A thorough investigation on the approximability and stability of the Lagrange multiplier discrete space is carried over to identify the correct LM space basis. The resulting method, although accurate and flexible, exhibits unreliable iterative convergence. To accelerate the iterative convergence, the Locally Exact Algebraic Preconditioner (LEAP), which is responsible for improving the information transfer between neighboring domains is introduced. The LEAP was conceived by carefully studying the properties of the Dirichlet-to-Neumann (DtN) map that is involved in the sub-structuring process of FETI. LEAP proceeds in a hierarchical way and directly factorizes the signular and near-singular interactions of the DtN map that arise from domain-face, domain-edge and domain-vertex interactions. For problems with small number of domains LEAP results in scalable implementations with respect to the discretization. On problems with large domain numbers, the numerical scalability can only be obtained through ``global'' preconditioners that directly convey information to remotely separated domains at every DDM iteration. The proposed ``global" preconditiong stage is based on the new Multigrid FETI (MG-FETI) method. This method provides a coarse grid correction mechanism defined in the dual space. Macro-basis functions, that satisfy thecurl-curl equation on each interface are constructed to reduce the size of the coarse problem, while maintaining a good approximation of the characteristic field modes. Numerical results showcase the performance of the proposed method on one-way, 2D and 3D decomposed problems, with structured and unstructured partitioning, conforming and non-conforming interface triangulations. Finally, challenging, real life computational examples showcase the true potential of the method.