A validation & verification driven ontology: An iterative process

Designing an ontology that meets the needs of end-users, e.g., a medical team, is critical to support the reasoning with data. Therefore, an ontology design should be driven by the constant and efficient validation of end-users needs. However, there is not an existing standard process in knowledge engineering that guides the ontology design with the required quality. There are several ontology design processes, which range from iterative to sequential, but they fail to ensure the practical application of an ontology and to quantitatively validate end-user requirements through the evolution of an ontology. In this paper, an ontology design process is proposed, which is driven by end-user requirements, defined as Competency Questions (CQs). The process is called CQ-Driven Ontology DEsign Process (CODEP) and it includes activities that validate and verify the incremental design of an ontology through metrics based on defined CQs. CODEP has also been applied in the design and development of an ontology in the context of a Mexican Hospital for supporting Neurologist specialists. The specialists were involved, during the application of CODEP, in collecting quality measurements and validating the ontology increments. This application can demonstrate the feasibility of CODEP to deliver ontologies with similar requirements in other contexts.

AMPLA

Software architecture design, when performed in context of agile software development (ASD), sometimes referred to as “agile architecting,” promotes the emerging and incremental design of the architectural artifact in a sense of avoiding “big design upfront” (BDUF). This chapter presents the Agile Modeling Process for Logical Architectures (AMPLA) method, an approach for supporting the emergence of a candidate (logical) architecture, rather than BDUF, the architecture in an early phase. The architecture then emerges throughout agile iterations, where AMPLA plays a key contribution for providing traceability between models, from the business need to service specifications, ranging from design stages to deployment, hence covering a software development life cycle (SDLC).

An overview of asphalt pavement design for streets and roads

Pavements are geotechnical problems; consequently, a geotechnical framework is useful to describe their constitutive elements. The design of asphalt pavements for streets and roads evolved from empiric to mechanistic-empiric (M-E) procedures throughout the 20th century. The mechanistic-empiric method, based on layered elastic theory, became a common practice with the publication of separate procedures by Shell Oil, Asphalt Institute, and French LCPC, among others. Since its origin, the M-E procedure can consider incremental pavement design but, only until the beginning of the 21st century, the computational power became available to practicing engineers. American MEPDG represents the state-of-the-art M-E incremental design procedure with significant advantages and drawbacks, the latter mainly related to the extensive calibration activities required to assure a proper analysis and design according to subgrade, climate, and materials at a particular location and for an intended level of reliability. Perpetual pavements are a subset of M-E designed pavements with a proven history of success for the particular conditions where they are warranted. No design method, either the most straightforward empirical approach or the most elaborated incremental mechanistic one, is appropriate without proper knowledge about the fundamental design factors and calibration of the performance models for each distress mode upon consideration.

Heuristic-Guided Solution Search Through a Two-Tiered Design Grammar

Grammar-based design is typically a gradual process; incremental design changes are performed until a problem statement has been satisfied. While they offer an effective means for searching a design space, standard grammars risk being computationally costly because of the iteration required, and the larger a given grammar the broader the search required. This paper proposes a two-tiered design grammar that enhances the computational design generation with generalized heuristics to provide a way to more efficiently search a design space. Specifically, this two-tiered grammar captures a combination of heuristic-based strategic actions (often observed in human designers) and smaller-scale modifications (common in traditional grammars). Rules in the higher tier are abstract and applicable across multiple design domains. Through associated guiding heuristics, these macrorules are translated down into a sequence of domain-specific, lower-tier microrules. This grammar is evaluated through an implementation within an agent-based simulated annealing team algorithm in which agents iteratively select actions from either the higher tier or the lower tier. This algorithm is used in two applications: truss generation, which is commonly used for testing engineering design methods, and wave energy converter design generation, which is currently a relevant research area in sustainable energy production. Comparisons are made between designs generated using only lower-tier rules and those generated using only higher-tier rules. Further tests demonstrate the efficacy of applying a combination of both lower-tier and higher-tier rules.