Manuel Noguera

Bio: Manuel Noguera is an academic researcher from University of Granada. The author has contributed to research in topics: Ontology (information science) & Business process modeling. The author has an hindex of 13, co-authored 91 publications receiving 580 citations.

Nutrition for Elder Care: a nutritional semantic recommender system for the elderly

Abstract: The awareness and familiarity of elderly people with the use of new technologies have increased considerably in the last few years, which consequently cause a higher willingness to the use of these technologies in their daily lives. This allows the elderly to benefit from technology through active and conscious participation in activities related to health, leisure and promotion of social relationships, fostering active ageing. Three large dimensions cover almost a major part of health care within the framework of early and intermediate stages of active ageing: physical exercise, healthy nutrition and cognitive stimulation. In this paper, we present a nutritional recommender system, Nutrition for Elder Care, intended to help elderly users to draw up their own healthy diet plans following the nutritional experts guidelines. The system has been developed with the intensive use of Semantic Web technologies pursuing knowledge sharing and reuse between different applications and agents and the discovering of implicit new knowledge.

A Communication Model to Integrate the Request-Response and the Publish-Subscribe Paradigms into Ubiquitous Systems

Abstract: The Request-Response (RR) paradigm is widely used in ubiquitous systems to exchange information in a secure, reliable and timely manner. Nonetheless, there is also an emerging need for adopting the Publish-Subscribe (PubSub) paradigm in this kind of systems, due to the advantages that this paradigm offers in supporting mobility by means of asynchronous, non-blocking and one-to-many message distribution semantics for event notification. This paper analyzes the strengths and weaknesses of both the RR and PubSub paradigms to support communications in ubiquitous systems and proposes an abstract communication model in order to enable their seamless integration. Thus, developers will be focused on communication semantics and the required quality properties, rather than be concerned about specific communication mechanisms. The aim is to provide developers with abstractions intended to decrease the complexity of integrating different communication paradigms commonly needed in ubiquitous systems. The proposal has been applied to implement a middleware and a real home automation system to show its applicability and benefits.

Zappa: An Open Mobile Platform to Build Cloud-Based m-Health Systems

Abstract: Cloud computing and associated services are changing the way in which we manage information and access data. E-health services are not impermeable to novel technologies, especially those that involve mobile devices. At present, many patient monitoring m-health (mobile-health) platforms consist of close, vendor-dependent solutions based on particular architectures and technologies offering a limited set of interfaces to interoperate with. This fact hinders to advance in quality attributes such as customization, adaptation, extension, interoperability and even transparency of cloud infrastructure of existing solutions according to the specific needs of their users (patients and physicians). This paper presents an extensible, scalable, highly-interoperable and customizable platform called Zappa, designed to support e-Health/m-Health systems and that is able to operate in the cloud. The platform is based on components and services architecture, as well as on open and close source hardware and open-source software that reduces its acquisition and operation costs. The platform has been used to develop several remote mobile monitoring m-health systems.

Pattern Recognition and Machine Learning

Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Challenges and improvements in distributed software development: a systematic review

Abstract: Distributed Software Development (DSD) has recently evolved, resulting in an increase in the available literature. Organizations now have a tendency to make greater development efforts in more attractive zones. The main advantage of this lies in a greater availability of human resources in decentralized zones at less cost. There are, however, some disadvantages which are caused by the distance that separates the development teams. Coordination and communication become more difficult as the software components are sourced from different places, thus affecting project organization, project control, and product quality. New processes and tools are consequently necessary. This work presents the findings of a systematic review of the literature related to the challenges concerning Distributed Software Development, whose purpose is to identify the solutions and improvements proposed up to the present day.