Pierfrancesco Bellini

Temporal logics for real-time system specification

The specification of reactive and real-time systems must be supported by formal, mathematically-founded methods in order to be satisfactory and reliable. Temporal logics have been used to this end for several years. Temporal logics allow the specification of system behavior in terms of logical formulas, including temporal constraints, events, and the relationships between the two. In the last ten years, temporal logics have reached a high degree of expressiveness. Most of the temporal logics proposed in the last few years can be used for specifying reactive systems, although not all are suitable for specifying real-time systems. In this paper we present a series of criteria for assessing the capabilities of temporal logics for the specification, validation, and verification of real-time systems. Among the criteria are the logics expressiveness, the logics order, presence of a metric for time, the type of temporal operators, the fundamental time entity, and the structure of time. We examine a selection of temporal logics proposed in the literature. To make the comparison clearer, a set of typical specifications is identified and used with most of the temporal logics considered, thus presenting the reader with a number of real examples.

Comparing fault-proneness estimation models

Over the last, years, software quality has become one of the most important requirements in the development of systems. Fault-proneness estimation could play a key role in quality control of software products. In this area, much effort has been spent in defining metrics and identifying models for system assessment. Using this metrics to assess which parts of the system are more fault-proneness is of primary importance. This paper reports a research study begun with the analysis of more than 100 metrics and aimed at producing suitable models for fault-proneness estimation and prediction of software modules/files. The objective has been to find a compromise between the fault-proneness estimation rate and the size of the estimation model in terms of number of metrics used in the model itself. To this end, two different methodologies have been used, compared, and some synergies exploited. The methodologies were the logistic regression and the discriminant analyses. The corresponding models produced for fault-proneness estimation and prediction have been based on metrics addressing different aspects of computer programming. The comparison has produced satisfactory results in terms of fault-proneness prediction. The produced models have been cross validated by using data sets derived from source codes provided by two application scenarios.

Km4City ontology building vs data harvesting and cleaning for smart-city services

Presently, a very large number of public and private data sets are available from local governments. In most cases, they are not semantically interoperable and a huge human effort would be needed to create integrated ontologies and knowledge base for smart city. Smart City ontology is not yet standardized, and a lot of research work is needed to identify models that can easily support the data reconciliation, the management of the complexity, to allow the data reasoning. In this paper, a system for data ingestion and reconciliation of smart cities related aspects as road graph, services available on the roads, traffic sensors etc., is proposed. The system allows managing a big data volume of data coming from a variety of sources considering both static and dynamic data. These data are mapped to a smart-city ontology, called KM4City (Knowledge Model for City), and stored into an RDF-Store where they are available for applications via SPARQL queries to provide new services to the users via specific applications of public administration and enterprises. The paper presents the process adopted to produce the ontology and the big data architecture for the knowledge base feeding on the basis of open and private data, and the mechanisms adopted for the data verification, reconciliation and validation. Some examples about the possible usage of the coherent big data knowledge base produced are also offered and are accessible from the RDF-Store and related services. The article also presented the work performed about reconciliation algorithms and their comparative assessment and selection.

Cooperative visual manipulation of music notation

As computer technologies and their potential emerging applications spread out, new needs have been detected for computer-based applications of music; cooperative music notation editing both in orchestras and music schools is one of them. This article is the only public document describing the details of cooperative work on music notation of MOODS (Music Object Oriented Distributed System). MOODS is a synchronous real-time cooperative editor for music scores. Its architecture includes mechanisms for troubleshooting conflicts in real-time, managing histories of commands and versioning, and for performing selective undo. The system also includes specific solutions in order to control the editing on the account of editing permission profiles. The most important aspects of MOODS associated with cooperative work on music notation scores are reported herein. The article highlights the general problems of cooperative systems and provides rationales for the solutions, which were found to build MOODS. The MOODS system has been implemented and validated thanks to the endeavor of several musicians in orchestras, music schools, and project partners. A prototype has been demonstrated in public at the Scala Theatre in Milan, Italy.

Optical music sheet segmentation

The optical music recognition problem has been addressed in several ways, obtaining suitable results only when simple music constructs are processed. The most critical phase of the optical music recognition process is the first analysis of the image sheet. The first analysis consists of segmenting the acquired sheet into smaller parts which may be processed to recognize the basic symbols. The segmentation module of the O/sup 3/ MR system (Object Oriented Optical Music Recognition) system is presented. The proposed approach is based on the adoption of projections for the extraction of basic symbols that constitute a graphic element of the music notation. A set of examples is also included.

Assessing Optical Music Recognition Tools

68 Computer Music Journal As digitization and information technologies advance, document analysis and optical-characterrecognition technologies have become more widely used. Optical Music Recognition (OMR), also commonly known as OCR (Optical Character Recognition) for Music, was first attempted in the 1960s (Pruslin 1966). Standard OCR techniques cannot be used in music-score recognition, because music notation has a two-dimensional structure. In a staff, the horizontal position denotes different durations of notes, and the vertical position defines the height of the note (Roth 1994). Models for nonmusical OCR assessment have been proposed and largely used (Kanai et al. 1995; Ventzislav 2003). An ideal system that could reliably read and “understand” music notation could be used in music production for educational and entertainment applications. OMR is typically used today to accelerate the conversion from image music sheets into a symbolic music representation that can be manipulated, thus creating new and revised music editions. Other applications use OMR systems for educational purposes (e.g., IMUTUS; see www.exodus.gr/imutus), generating customized versions of music exercises. A different use involves the extraction of symbolic music representations to be used as incipits or as descriptors in music databases and related retrieval systems (Byrd 2001). OMR systems can be classified on the basis of the granularity chosen to recognize the music score’s symbols. The architecture of an OMR system is tightly related to the methods used for symbol extraction, segmentation, and recognition. Generally, the music-notation recognition process can be divided into four main phases: (1) the segmentation of the score image to detect and extract symbols; (2) the recognition of symbols; (3) the reconstruction of music information; and (4) the construction of the symbolic music notation model to represent the information (Bellini, Bruno, and Nesi 2004). Music notation may present very complex constructs and several styles. This problem has been recently addressed by the MUSICNETWORK and Motion Picture Experts Group (MPEG) in their work on Symbolic Music Representation (www .interactivemusicnetwork.org/mpeg-ahg). Many music-notation symbols exist, and they can be combined in different ways to realize several complex configurations, often without using well-defined formatting rules (Ross 1970; Heussenstamm 1987). Despite various research systems for OMR (e.g., Prerau 1970; Tojo and Aoyama 1982; Rumelhart, Hinton, and McClelland 1986; Fujinaga 1988, 1996; Carter 1989, 1994; Kato and Inokuchi 1990; Kobayakawa 1993; Selfridge-Field 1993; Ng and Boyle 1994, 1996; Couasnon and Camillerapp 1995; Bainbridge and Bell 1996, 2003; Modayur 1996; Cooper, Ng, and Boyle 1997; Bellini and Nesi 2001; McPherson 2002; Bruno 2003; Byrd 2006) as well as commercially available products, optical music recognition—and more generally speaking, music recognition—is a research field affected by many open problems. The meaning of “music recognition” changes depending on the kind of applications and goals (Blostein and Carter 1992): audio generation from a musical score, music indexing and searching in a library database, music analysis, automatic transcription of a music score into parts, transcoding a score into interchange data formats, etc. For such applications, we must employ common tools to provide answers to questions such as “What does a particular percentagerecognition rate that is claimed by this particular algorithm really mean?” and “May I invoke a common methodology to compare different OMR tools on the basis of my music?” As mentioned in Blostein and Carter (1992) and Miyao and Haralick (2000), there is no standard for expressing the results of the OMR process. Assessing Optical Music Recognition Tools

Managing music in orchestras

The typical orchestra manages a huge amount of information. A symphonic works main score often runs to more than 100 pages, while an operatic score can run 600 or more. From the main score, the conductor draws some 15 to 30 different instrumental parts and distributes them to 40 or more lecterns so that 70 musicians can play from them during rehearsals and performances. This overhead increases significantly if the piece requires a chorus as well. A typical performance ranges from a few minutes to more than two hours. Individual musicians often make simple changes to the score, writing them manually on their parts during rehearsals, most often by adding interpretation symbols such as dynamics, expression marks, and string bowings. More complex changes-such as arrangements for different instruments, transpositions, and the deletion or addition of music sections-must be decided by the conductor. Operas, ballets, and new symphonic works frequently require such time-consuming modifications. Many performing organizations and publishers could benefit from a computerized option that allows storage of multiple versions and reduces the amount of repetitive work involved. The authors discuss their approach: the Music Object-Oriented Distributed System.

Linked open graph

A number of accessible RDF stores are populating the linked open data world. The navigation on data reticular relationships is becoming every day more relevant. Several knowledge base present relevant links to common vocabularies while many others are going to be discovered increasing the reasoning capabilities of our knowledge base applications. In this paper, the Linked Open Graph, LOG, is presented. It is a web tool for collaborative browsing and navigation on multiple SPARQL entry points. The paper presented an overview of major problems to be addressed, a comparison with the state of the arts tools, and some details about the LOG graph computation to cope with high complexity of large Linked Open Dada graphs. The LOG.disit.org tool is also presented by means of a set of examples involving multiple RDF stores and putting in evidence the new provided features and advantages using dbPedia, Getty, Europeana, Geonames, etc. The LOG tool is free to be used, and it has been adopted, developed and/or improved in multiple projects: such as ECLAP for social media cultural heritage, Sii-Mobility for smart city, and ICARO for cloud ontology analysis, OSIM for competence/knowledge mining and analysis. LOG tool provides a large number of new features for managing LDs on web.Understanding RDF storesi s becoming a fundamental skill.Exploiting linked data without copying them locally is becoming a must.Managing complexity of Linked Data on web is needed.

Symbolic music representation in MPEG

With the spread of computer technology into the artistic fields, new application scenarios for computer-based applications of symbolic music representation (SMR) have been identified. The integration of SMR in a versatile multimedia framework such as MPEG will enable the development of a huge number of new applications in the entertainment, education, and information delivery domains.

Expressing and organizing real-time specification patterns via temporal logics

Formal specification models provide support for the formal verification and validation of the system behaviour. This advantage is typically paid in terms of effort and time spent in learning and using formal methods and tools. The introduction and usage of patterns have a double impact. They stand for examples on how to cover classical problems with formal methods in many different notations, so that the user can shorten the time to understand if a formal method can be used to meet his purpose and how it can be used. Furthermore, they are used for shortening the specification time, by reusing and composing different patterns to cover the specification, thus producing more understandable specifications which refer to commonly known patterns. For these reasons, both interests in and usage of patterns are growing and a higher number of proposals for patterns and pattern classification/organization has appeared in the literature. This paper reports a review of the state of the art for real-time specification patterns, so as to organize them in a unified way, while providing some new patterns which complete the unified model. The proposed organization is based on some relationships among patterns as demonstrated in the paper. During the presentation the patterns have been formalized in TILCO-X, whereas in appendix a list of patterns with formalizations in several different logics such as TILCO, LTL, CTL, GIL, QRE, MTL, TCTL and RTGIL, is provided disguised as links to the locations where such formalizations can be recovered and/or are directly reported, if found not accessible in the literature; this allows the reader to have a detailed view of all the classified patterns, including the ones already added. Furthermore, an example has been proposed to highlight the usefulness of the new identified patterns completing the unified model.