On the use of textural features for writer identification in old handwritten music scores

Writer identification consists in determining the writer of a piece of handwriting from a set of writers. In this paper we present a system for writer identification in old handwritten music scores which uses only music notation to determine the author. The steps of the proposed system are the following. First of all, the music sheet is preprocessed for obtaining a music score without the staff lines. Afterwards, four different methods for generating texture images from music symbols are applied. Every approach uses a different spatial variation when combining the music symbols to generate the textures. Finally, Gabor filters and Grey-scale Co-ocurrence matrices are used to obtain the features. The classification is performed using a k-NN classifier based on Euclidean distance. The proposed method has been tested on a database of old music scores from the 17th to 19th centuries, achieving encouraging identification rates.

Monte Carlo modeling of polarized light propagation: Stokes vs Jones - Part II

In this second part of our comparative study inspecting the (dis)similarities between “Stokes” and “Jones,” we present simulation results yielded by two independent Monte Carlo programs: (i) one developed in Bern with the Jones formalism and (ii) the other implemented in Ulm with the Stokes notation. The simulated polarimetric experiments involve suspensions of polystyrene spheres with varying size. Reflection and refraction at the sample/air interfaces are also considered. Both programs yield identical results when propagating pure polarization states, yet, with unpolarized illumination, second order statistical differences appear, thereby highlighting the pre-averaged nature of the Stokes parameters. This study serves as a validation for both programs and clarifies the misleading belief according to which “Jones cannot treat depolarizing effects.”

How Do Software Architects Specify and Validate Quality Requirements?

Software architecture is the result of a design effort aimed at ensuring a certain set of quality attributes. As we show, quality requirements are commonly specified in practice but are rarely validated using automated techniques. In this paper we analyze and classify commonly specified quality requirements after interviewing professionals and running a survey. We report on tools used to validate those requirements and comment on the obstacles encountered by practitioners when performing such activity (e.g., insufficient tool-support; poor understanding of users needs). Finally we discuss opportunities for increasing the adoption of automated tools based on the information we collected during our study (e.g., using a business-readable notation for expressing quality requirements; increasing awareness by monitoring non-functional aspects of a system).

Dicto: A Unified DSL for Testing Architectural Rules

Software architecture consists of a set of design choices that can be partially expressed in form of rules that the implementation must conform to. Architectural rules are intended to ensure properties that fulfill fundamental non-functional requirements. Verifying architectural rules is often a non- trivial activity: available tools are often not very usable and support only a narrow subset of the rules that are commonly specified by practitioners. In this paper we present a new highly-readable declarative language for specifying architectural rules. With our approach, users can specify a wide variety of rules using a single uniform notation. Rules can get tested by third-party tools by conforming to pre-defined specification templates. Practitioners can take advantage of the capabilities of a growing number of testing tools without dealing with them directly.

Dicto: Keeping Software Architecture Under Control

Dicto is a declarative language for specifying architectural rules using a single uniform notation. Once defined, rules can automatically be validated using adapted off-the-shelf tools.