Actualmente, hay muchas aplicaciones que tienen como objetivo mejorar la adherencia terapéutica (por ejemplo, sensores ingeribles). Sin embargo, todavía existen limitaciones y desafíos para hacer que estas aplicaciones sean más adaptables a las necesidades reales de los usuarios. Además, actualmente hay muchos dispositivos(sensores) para colectar datos fisiológicos (e.g., Moodmetric), por lo tanto, los servicios de atención medica pueden explotar las señales biométricas para comprender mejor las necesidades de los usuarios. En esta tesis se propone mejorar la adherencia terapéutica en personas mayores con diagnóstico de hipertensión. Para hacer esto, se propone una aplicación móvil adaptativa y persuasiva (llamada Health Care Remin- der ), la cual reconoce las emociones del usuario (i.e., estrés) a partir de datos fisiológicos (actividad electrodermal). Con esta informaci...

In order to facilitate 3D object processing, it is common to use high-level representations such as local descriptors that are usually computed using defined neighborhoods. K-rings, a technique to define them, is widely used by several methods. In this work, we propose a model for the distributed computation of local descriptors over 3D triangular meshes, using the concept of k-rings. In our experiments, we measure the performance of our model on huge meshes, evaluating the speedup, the scalability, and the descriptor computation time. We show the optimal configuration of our model for the cluster we implemented and the linear growth of computation time regarding the mesh size and the number of rings. We used the Harris response, which describes the saliency of the object, for our tests.

Finally, I would like to thank in a special way to the National Council for Science, Technology and Technological Innovation (CONCYTEC-PERU) and to the National Fund for Scientific Development, Technological and Technological Innovation (FONDECYTCIENCIACTIVA), which through the Management Agreement 234-2015-FONDECYT have allowed the grant and financing of my studies in the Master Program in Computer Science at Universidad Cat´olica San Pablo (UCSP).

Stress in cattle is one of the main factors that generate economic losses in the livestock sector (e.g., reduction in the quality of milk or meat). In this field, heat stress has been considered as one of the main types of stress that negatively affects cattle. In addition, thanks to the arising of the Internet of Things in Animal Health, some researchers have proposed systems and models for the detection of this type of stress in an automated way, collecting and using data from meteorological variables (e.g., temperature, humidity), heart rate and others. However, the proposed models are mainly focused on heat stress detection that uses threshold-based estimation to determine the presence of stress; but, the level of stress experienced by cows can vary depending on their breed, or their ability to adapt to the environment where they are located. Therefore, in this project we propose an ...

As more actions are needed to reduce the current gap in leadership positions in STEM and IT, it is important to systematically study existing policies and programs that promote gender equality. This research-in-progress (RIP) presents the status of one of the research activities of a larger ongoing project that seeks to advance impact research about women's leadership in STEM fields in low- and middle-income countries (LMICs) in Latin America. Specifically, this study uses two approaches: (a) gray literature search, and (b) systematic literature review search in four recognized citation databases to identify the obtaining crosscountry comparable data to assess policies and interventions to reduce the gender gap in STEM. Researchers and policy makers interested in policies that promote female participation and gender equality will benefit from the results of this study.