Negotiating Temporal Commitments in Cross-Organizational Business Processes

Cross-organizational business processes emerge from the cooperation of intra-organizational business processes through exchange of messages. The involved parties agree on communication protocols, which contain in particular temporal constraints: as obligations on one hand, and as guarantees on the other hand. These constraints form also requirements for the design of the hidden implementation of the processes and are the basis for control decisions for each party. We present a comprehensive methodology for modeling the temporal aspects of cross-organizational business processes, checking dynamic controllability of such processes, and supporting the negotiation of temporal commitments. We do so by computing the consequences of temporal constraints in choreographies, and by computing the weakest preconditions for the dynamic controllability of a participating process

Model and Simulation of dynamics of myeloma growth

ilustraciones, diagramasEn este trabajo se presentan tres capítulos con modelos in-silico desarrollados a través de ecuaciones diferenciales y solucionados computacionalmente, que proporcionan una perspectiva del acoplamiento entre el ciclo de remodelación ósea y las poblaciones tumorales. Comprender las dinámicas entre el tejido sano, las células que realizan el proceso de remodelación y las diferentes patologías, como el osteosarcoma o los tumores metastásicos, es fundamental para crear estrategias m´as personalizadas y especializadas para mitigar los efectos de estas enfermedades o curarlas por completo. Los modelos presentados proveen información mas detallada de la dinámica real de la remodelación ósea en pacientes por masas tumorales. Ofrecen un marco innovador y una base solida para el desarrollo de nuevos modelos, herramientas y técnicas que permitan el desarrollo de la medicina personalizada, con una perspectiva mas completa y controlada de los procesos fisiológicos y patológicos. Se espera que en el futuro, estos modelos sean aun mas robustos y versátiles, brindando un mayor apoyo para la toma de decisiones mas acertadas en cada caso clínico particular. (Texto tomado de la fuente).This work presents three chapters with in-silico models developed through differential equations and computationally solved, providing a perspective of the coupling between the bone remodeling cycle and tumor populations. Understanding the dynamics between healthy tissue, cells involved in the remodeling process, and different pathologies, such as osteosarcoma or metastatic tumors, is fundamental for creating more personalized and specialized strategies to mitigate the effects of these diseases or cure them completely. The models presented provide more detailed information about the real dynamics of bone remodeling in patients with tumor masses. They offer an innovative framework and a solid foundation for the development of new models, tools, and techniques that enable personalized medicine, with a more comprehensive and controlled perspective of physiological and pathological processes. It is expected that in the future, these models will become even more robust and versatile, providing greater support for making more accurate decisions in each specific clinical case.MaestríaMagíster en Ingeniería MecánicaIngeniería de diseño y biomecánic

A Computational study of sparse or structured matrix operations

Matrix computation is an important area in high-performance scientific computing. Major computer manufacturers and vendors typically provide architecture- aware implementation libraries such as Basic Linear Algebra Subroutines (BLAS). In this thesis, we perform an experimental study of a subset of matrix operations, where the matrices are dense, sparse, or structured in Java. We implement a subset of BLAS operations in Java and compare their performance with standard data structures Compressed Row Storage (CRS) and Java Sparse Array (JSA) for dense and sparse structured matrices. The diagonal storage format is shown to be a viable alternative for dense and structured matrices