This chapter investigates service-oriented simulation frameworks from the ontological, epistemological, and teleological perspectives. First, we give an overview of various specific frameworks that imply particular referential ontological, epistemological, and teleological perspectives for real world systems. Then we combine the partial considerations derived from the review into a unifying fra...

Following the development of a unifying and transparent approach to grading the certainty of evidence and strength or recommendations, the GRADE (Grading of Recommendations Assessment, Development and Evaluation) Working Group has refined its process of moving from Evidence to Decisions. The purpose of its new Evidence to Decision (EtD) frameworks is to help people use evidence in a structured ...

We present Brook, a new framework for distributed machine learning problems. Like some previous frameworks, Brook adopts the parameter server paradigm that simplifies the task of distributed programming. Unlike these frameworks, we build a novel system component called parameter agent that masks the communication details between workers and servers by mapping remote servers to local in-memory f...

Effective evaluation of healthcare information systems is necessary in order to ensure systems adequately meet the requirements and information processing needs of the users and healthcare organisations. A number of studies have proposed evaluation frameworks to aid in evaluation work. However, some of them can be improved upon. This paper proposes a novel evaluation model to evaluate user acce...

Indigenous evaluation frameworks have not been investigated in the context of American Indian and Alaska Native (AI/AN) physical activity programs, an important area given the relationship between effective physical activity programs and quality of life among these populations. To address this gap, staff members of AI/AN physical activity programs were interviewed to explore their understanding...

This survey report overviews recent frameworks on face recognition and retrieval solutions for videos search and surveillance applications. We introduce an engineering of a bland framework for facial detection, retrieval and recognition in video and audit scholarly frameworks reported in the scholastic writing suitable for videos search and surveillance applications. Suggestions on the choice o...

This paper proposes optimization frameworks for discrete road network design considering the land-use transport interaction over time. Unlike existing models, the optimization frameworks can determine the optimal designs automatically without trial-and-error once the objective(s) is/are clearly defined. Moreover, these frameworks allow the evaluation of the impacts of the optimal designs on the...

The popularity of Big Data computing models like MapReduce has caused the emergence of many frameworks oriented to High Performance Computing (HPC) systems. The suitability of each one to a particular use case depends on its design and implementation, the underlying system resources and the type of application to be run. Therefore, the appropriate selection of one of these frameworks generally ...

For some years now, Meta-Heuristic methods have demonstrated their ability to tackle large-scale optimisation problems. Up to now, several frameworks have been implemented for this family of methods. Some of them are either dedicated to Local Search such as EasyLocal++[5], Localizer[8], LocalSearch framework[1], Templar[7], HotFrame[4] or to Evolutionary Computation such as EOS[2], EASEA[3]. Th...

The growing need for 'intelligent' video retrieval systems leads to new architectures combining multiple characterizations of the video content that rely on highly expressive frameworks while providing fully-automated indexing and retrieval processes. As a matter of fact, addressing the problem of combining modalities within expressive frameworks for video indexing and retrieval is of huge impo...