The growing complexity and the increasing diffusion of applications exploiting both the Internet of Things (IoT) and the Web of Things (WoT) paradigms have led to the necessity of ensuring robust security and reciprocal trust in the management of huge amount of data from heterogeneous sources. The blockchain technology can satisfy these requirements, ensuring data integrity, univocity, and immutability of the data shared and saved in distributed IoT/IoW systems. In this paper, a deep analysis of requirements for Blockchain based IoT/WoT frameworks has been conducted. The main contributions include (i) formal implications of certifying integrity for data models and for the usage/certification of corresponding instances of entities/ devices and their time series messages in a platform that may present both non-certified and certified models, entities and data messages; (ii) automation of certification and verification processes, which implies mechanisms and formal rules; (iii) flexible certification of data messages enforcing efficiency and sustainability; (iv) support for multi-organization distributed solutions; (v) performance assessment . The solution has been validated with the interconnection to a private/permissioned blockchain developed using Hyperledger Fabric, while enforcing the solution on Snap4City federated network of platforms for applications in the domain of mobility. The research has been performed in the context of CN MOST, which is the national center on Sustainable Mobility in Italy, and within its flagship action OPTIFaaS.

Addressing mobility and transport problems is nowadays of paramount importance for any city due to the increasing urbanization. Traffic congestion, pollutant emissions, energy consumption are some of the problems related to urban mobility. Therefore, there is the need of tools able to support decision-makers in studying, evaluating, and planning sustainable urban evolutions. A few open-source and proprietary solutions are available requiring on-premises installations, large effort, and providing limited capabilities to actually handle real-time data (from data spaces, and standards). Moreover, they are limited in terms of analytic integration and do not offer automatic generation of suggestions. In practice they do not manage the explosion of complexity regarding computational and storage/models aspects. For these reasons, this paper presents a comprehensive architecture for a Smart City Digital Twin platform, specifically designed to support mobility and transportation decision-making through advanced what-if analysis and optimization. The platform, integrated within the Snap4City system, enables real-time data processing and complex analytics to create virtual urban environments for evaluating potential infrastructure changes. Through microservice architecture, the platform supports massive data ingestion, scenario creation, and predictive modelling, facilitating both short-term and long-term planning. The solution leverages artificial intelligence (AI), machine learning (ML), and reinforcement learning (RL) to optimize city operations and suggest actionable insights, aiding city planners in strategic and tactical decisions. This architecture has been validated through implementations in Italian cities, demonstrating scalability and flexibility to accommodate diverse urban needs and improve traffic flow, energy efficiency, and environmental impact. This work has been performed in the context of OPTIFaaS Flagship of CN MOST, the National Centre for Sustainable Mobility in Italy, and for CN HPC Big Data and Quantum Computing, ICSC.

Abstract Recently, Digital Twins solutions have attracted a growing interest as a fundamental paradigm for managing data driven processes on smart cities. They are complex modelling that should include 3D interactive representations of buildings and infrastructures, integrated with a wide range of data for Smart City cyber-physical ecosystem monitoring and controlling. This paper presents a framework for modelling, generating and distributing Digital Twin representations with 3D models from a various set of data, as well as its integration into the open-source Smart City framework, where many kinds of real time and historical data are available. The proposed solution offers a method for creating integrated data rendering of 3D city entities coupled with Smart City data (e.g., IoT Devices with time-series and historical data, heatmaps, geometries and shapes related to traffic flows, bus routes/stops, cycling paths). The solution for generating 3D representation is based on a number of computer vision and machine learning solutions, thus shortening the activities of passing from raw data (i.e., Lidar, shapes, patterns, etc.) to 3D representations. Implementation has been enforced into the quite widespread open-source Snap4City Smart City platform and has been validated by using hundreds of buildings in Florence city central area, Italy, plus hundreds of thousands of data as points of interest, IoT Devices, traffic flows, dynamic heatmaps, etc.

A range of new kind of applications are growing for the integration of different technologies and needs such as IoT/IoE (Internet of Things/Everything), WoT (web of things), Digital twins and smart data models, data spaces. These applications demand less attention to the storage modeling since the adopted big data stores are less structured. Therefore, the connection from data storage to visual representation can be more automated. All these aspects open the path for rapid prototyping. In this paper a fast-prototyping development lifecycle for that category of smart applications is proposed. The proposed solution works on heterogeneous data types, push and pull, wide interoperability, covering all aspects from data ingestion to front-end. It can be regarded as a specific declination of AGILE development paradigm in which several activities have been strongly shortened by exploiting a number of modelling facilities of the development environment and technologies. The proposed development lifecycle was defined and tuned for the Snap4City platform, which provides an integrated development environment for rapid prototyping of smart application based on low coding, including visual programming, and a number of visual tools for creating the applications. The solution has been validated in the context of multiple interconnected scenarios of several large-scale projects and pilots such as Herit-Data, Panacea, Resolute, Replicate, TRAFAIR, etc.

Fashion retail has a large and ever-increasing popularity and relevance, allowing customers to buy anytime finding the best offers and providing satisfactory experiences in the shops. Consequently, Customer Relationship Management solutions have been enhanced by means of several technologies to better understand the behaviour and requirements of customers, engaging and influencing them to improve their shopping experience, as well as increasing the retailers' profitability. Current solutions on marketing provide a too general approach, pushing and suggesting on most cases, the popular or most purchased items, losing the focus on the customer centricity and personality. In this paper, a recommendation system for fashion retail shops is proposed, based on a multi clustering approach of items and users' profiles in online and on physical stores. The proposed solution relies on mining techniques, allowing to predict the purchase behaviour of newly acquired customers, thus solving the cold start problems which is typical of the systems at the state of the art. The presented work has been developed in the context of Feedback project partially founded by Regione Toscana, and it has been conducted on real retail company Tessilform, Patrizia Pepe mark. The recommendation system has been validated in store, as well as online.

Smart cities are distributed heterogeneous systems of systems connected to each other via a variety of heterogeneous data streams involving multiple stakeholders and organizations. This complexity is reflected also in the data that have to be managed to provide a concrete and useful real time service to the citizens. The data ingestion phase is critical for the whole services, since it has to preserve the information, connect the new data with old data and establish right connections with city entities. This paper describes data ingestion and inspection in the Snap4City open source scalable Smart aNalytic APplication builder, with a specific focus on how heterogeneous data is represented, how its quality is inspected, and how to develop ingestion procedures in an efficient manner. The Snap4City ingestion processes are based on a semantic and unified data ingestion model, capable of aggregating different types of data. A performance comparison of different data ingestion modalities is presented.

Smart Cities are probably on the more complex environment for IOT data collection. IOT data could have different producers, sample rates, periodic and aperiodic, typical trends, structures and stacks, faults, etc. Thus, a strongly flexible and scalable solution is needed to avoid investing huge amount of resources in anomaly detection that has to be done in real time and has to be agnostic to the above-mentioned problems. This paper presents a solution for automatic detection of anomalies. The proposed approach scales seamlessly and integrates in different contexts, featuring different sensor types, protocols, and data formats, and computationally cheap. The research has been developed in the context of Snap4City PCP Select4Cities project and is presently implemented in the Https://www.snap4city.org solution adopted in several cities and regions.

In the context of Smart City, it is quite frequent the usage of Smart City API for providing services at web and mobile applications. Most of the solutions using Smart City APIs are focused on a single city. This means that passing from one city/area to another, the users must change application. This happens for the lack of interoperability among Smart City APIs and/or services. In this paper, the problem of federation of smart city services is addressed by proposing a solution for federating smart city APIs. To this end, a formal model has been proposed to federate API services, with efficiency, security, scalability, and capacity of managing overlapped areas of competence, distributed searches, etc. These features are typically not all satisfied by classic GIS solutions which federate the services at level of databases. The solution has been developed in the context of Snap4City European platform enhancing former Km4City API of Sii-Mobility national project with Snap4City (https://www.snap4city.org).

Real time traffic flow data in terms of road-segments traffic densities are relevant information at the basis of several smart services, such as smart routing, smart planning for evacuations, planning of civil works on the city, etc. The traditional methods for traffic flow measured via sensors using data from navigator Apps (e.g., TomTom, Google map, Waze) could be very expensive to be acquired. For this reason, there is the space for low cost and fast solutions for dense traffic flow reconstruction from scattered data coming from a limited number of street sensors spread on the city. The proposed method is based on differential equations and physical constraints applied to a detailed street graph which is enriched of several features. A stochastic learning approach has been adopted to estimate the weights representing in certain sense the road-segments capacity at each time slot of the day. The proposed solution allows computing in real-time the traffic density reconstruction in unmeasured road-segments. The solution has been validated estimating the error in the places where the sensors are positioned, excluding each of them iteratively and reconstructing the flow without it. Then, it has been possible to estimate the error between the reconstructed traffic density and the measured values. This approach allowed setting up a converging algorithm for estimating the traffic density in the whole city graph from detailed parameters. The proposed reconstruction model has been created by exploiting open and real-time data in the context of Sii-Mobility research project by using Km4City infrastructure in the area of Florence, Italy, for its corresponding Smart City solution.

The new challenges in the smart city context are mainly related to the stimulation of the city users towards taking more sustainable behaviors, in mobility and energy. The state of the art in this case is mainly focused on classical smart city solution for informing the city users and or for engaging them with specific wired rules toward virtuous models. And not using flexible languages and predictive models, pushing them towards a larger range of virtuous habits. On this regards, the main problems are the computation of user behavior via data analytic (semantic computing, machine learning), as well as the formalization of strategies via simple and well formalized language for producing engagements to the city users, which can be understood by city operators. In this paper, a solution for city users engagement is studied and implemented for Sii-Mobility Smart city national project in Italy has been presented. The solution has been implemented thanks to the exploitation of Km4City model and semantic computing. The paper also presents the validation of results about the effective usage of the solution by providing some statistical evidence about the efficient assessment of user behavior and of engagement rules acceptance rate.

The main technical issues regarding smart city solutions are related to data gathering, aggregation, reasoning, data analytics, access, and service delivering via Smart City APIs (Application Program Interfaces). Different kinds of Smart City APIs enable smart city services and applications, while their effectiveness depends on the architectural solutions to pass from data to services for city users and operators, exploiting data analytics, and presenting services via APIs. Therefore, there is a strong activity on defining smart city architectures to cope with this complexity, putting in place a significant range of different kinds of services and processes. In this paper, the work performed in the context of Sii-Mobility smart city project on defining a smart city architecture addressing a wide range of processes and data is presented. To this end, comparisons of the state of the art solutions of smart city architectures for data aggregation and for Smart City API are presented by putting in evidence the usage semantic ontologies and knowledge base in the data aggregation in the production of smart services. The solution proposed aggregate and re-conciliate data (open and private, static and real time) by using reasoning/smart algorithms for enabling sophisticated service delivering via Smart City API. The work presented has been developed in the context of the Sii-Mobility national smart city project on mobility and transport integrated with smart city services with the aim of reaching a more sustainable mobility and transport systems. Sii-Mobility is grounded on Km4City ontology and tools for smart city data aggregation, analytics support and service production exploiting smart city API. To this end, Sii-Mobility/Km4City APIs have been compared to the state of the art solutions. Moreover, the proposed architecture has been assessed in terms of performance, computational and network costs in terms of measures that can be easily performed on private cloud on premise. The computational costs and workloads of the data ingestion and data analytics processes have been assessed to identify suitable measures to estimate needed resources. Finally, the API consumption related data in the recent period are presented.

The main technical issues regarding smart city solutions are related todata gathering, aggregation, reasoning, access, and service delivering via Smart City APIs (Application Program Interfaces). Aggregated and re-conciliated data (open and private, static and real time) should be exploitable by reasoning/smart algorithms for enabling sophisticated service delivering. Different kinds of Smart City APIs enable Smart City Services and Applications, while their effectiveness depends on the architectural solutions to pass from data to services for city users and operators. To this end, a comparison of the state of the art solutions for data aggregation was performed, by putting in evidence the needs of semantic interoperable aggregated data, to provide smart services. This paper presents the work performed in the context of the Sii-Mobility national smart city project on mobility and transport integrated with services. Sii-Mobility is grounded on Km4City ontology and tools for smart city data aggregation and service production. To this end, Sii-Mobility/Km4City APIs have been compared to the state of the art solutions. Finally, the API consumption related data in the recent period are presented.

The complexity of Cloud infrastructures is increasing every year, requiring new concepts and tools to face off topics such as process configuration and reconfiguration, automatic scaling, elastic computing and healthiness control. This paper presents a Smart Cloud solution based on a Knowledge Base, KB, with the aim of modeling cloud resources, Service Level Agreements and their evolution, while enabling the reasoning on cloud structures and implementing strategies of efficient smart cloud management and intelligence. The solution proposed is composed of Smart Cloud Engine, SCE, the Knowledge Base, KB, and the Supervisor and Monitoring module for data acquisition. It can be easily integrated with any cloud configuration manager, cloud orchestra or, and monitoring tool, since the connections with these tools are performed by using REST calls and XML files.

Multimedia services of cultural institutions need to be supported by content, metadata and workflow management systems to efficiently manage huge amount of content items and metadata production. Online digital libraries and cultural heritage institutions, as well as portals of publishers need an integrated multimedia back office in order to aggregate content collection and provide them to national and international aggregators, with respect to Intellectual Property Rights, IPR. The aim of this paper is to formalize and discuss requirements, modeling, design and validation of an institutional aggregator for metadata and content, coping with IPR Models for conditional access and providing content towards Europeana, the European international aggregator. This paper presents the identification of the Content Aggregator requirements for content management and IPR, and thus the definition and realization of a corresponding distributed architecture and workflow solution satisfying them. The main contributions of this paper consist of the formalization of IPR Model that enable the shortening of the activities for the IPR resolution, and avoid the assignment of conflicting rights/permissions during IPR model formalization, and thus of licensing. The proposed solution, models and tools have been validated in the case of the ECLAP service and results are reported in the paper. ECLAP Content Aggregator has been established by the European Commission to serve Europeana for the thematic area of Performing Arts institutions.

The modeling of performing arts metadata is considered one of the most challenging problems, since performances add complexities related to events to the classical cultural heritage descriptors associated to physical objects. The most relevant lacks of the present models are related to the modeling of information connected to performers and performances, which are obviously distinguishing aspects of the performing arts and are essential for the preservation of our cultural heritage and literature, such aspects being strongly connected with performing arts. This paper presents the European Collected Library of Artistic Performance (ECLAP) semantic model that has been specifically defined for aggregating and enriching performing arts content coming from several content providers. ECLAP has been set up by the European Commission to play the role of content aggregator for Europeana. The proposed ECLAP semantic model addresses most of the identified problems. The proposed model has been compared with present standards and it is now supported by a graphic tool for user navigation among semantic relationships and Linked Open Data (LOD). The paper also describes the generation of LOD from the ECLAP semantic model and the mapping of ECLAP model to Europeana Data Model (EDM). The experience highlighted that some relevant elements produced, enriched and aggregated by ECLAP cannot be mapped into EDM, while the ECLAP model can address some of the details related to the performing arts which are not at present addressed by the available standards.

There are several education and training cases where multi-camera view is a traditional way to work: performing arts and news, medical surgical actions, sport actions, instruments playing, speech training, etc. In most cases, users need to interact with multi camera and multi audiovisual to create among audiovisual segments their own relations and annotations with the purpose of: comparing actions, gesture and posture; explaining actions; providing alternatives, etc. Most of the present solutions are based on custom players and/or specific applications which force to create custom streams from server side, thus leading to restrictions on the user activity as to establishing dynamically additional relations. Web based solutions would be more appreciated and are complex to be realized for the problems related to the video desynchronization. In this paper, MyStoryPlayer/ECLAP solution is presented. The major contributions to the state of the art are related to: (i) the semantic model to formalize the relationships and play among audiovisual determining synchronizations, (ii) the model and modality to save and share user experiences in navigating among lessons including several related and connected audiovisual, (iii) the design and development of algorithm to shorten the production of relationships among media, (iv) the design and development of the whole system including its user interaction model, and (v) the solution and algorithm to keep the desynchronizations limited among media in the event of low network bandwidth. The proposed solution has been developed for and it is in use within ECLAP (European Collected Library of Performing Arts) for accessing and commenting performing arts training content. The paper also reports validation results about performance assessment and tuning, and about the usage of tools on ECLAP services. In ECLAP, users may navigate in the audiovisual relationships, thus creating and sharing experience paths. The resulting solution includes a uniform semantic model, a corresponding semantic database for the knowledge, a distribution server for semantic knowledge and media, and the MyStoryPlayer Client for web applications.

Presently a very large number of public and private data sets are available around the local governments. In most cases, they are not semantically interoperable and a huge human effort is needed to create integrated ontologies and knowledge base for smart city. In this paper, a system for the ingestion of data for smart city related aspects as road graph, services available on the roads, traffic sensors etc., is proposed. The system allows to manage a big volume of data coming from a variety of sources considering both static and dynamic data, these data are then mapped to a smart-city and mobility ontology and stored into an RDF-Store where this data are available for applications via SPARQL queries to provide new services to the users. The paper presents the knowledge base and the mechanisms adopted for the verification, reconciliation and validation. Some examples about the possible usage of the knowledge base produced are also offered and are accessible from the RDF-Store.

Digital rights management solutions are today quite widespread. Their cost is still quite expensive, and thus in many cases, their application is limited to specific business cases. On the other hand, the market still offers large cases where scalable DRM solutions would find their applicability, for example the management of complex cross media content such as the one used for the educational content, for electronic medical record, etc. In this paper, the focus is on reducing DRM costs by solving scalability problems lying behind the complexity of granting authorizations and performing verification for a large number of users, content and rights associated with them. The proposed solution is based on the exploitation of the DHT P2P network and storage to cope with verification and grant authorization. The paper reports the structure of the DRM solutions, the details for including the DHT P2P into the DRM architecture. The paper also reports details on how the proposed P2P DRM solution can be integrated into traditional DRM solutions. The provided experimental results have proved the reduction of costs, the scalability against the aforementioned cases. The studies and solutions reported in this paper have been worked out and validated on top of MPEG-21/AXMEDIS DRM solutions and tools. On the other hand, the solution is general enough to be adapted in other DRM solutions.

Despite the presence of many systems for developing and managing structured taxonomies and/or SKOS models for a given domain for which small documents set are accessible, the production and maintenance of these domain knowledge bases is still a very expensive and time consuming process. This paper proposes a solution for assisting expert users in the development and management of knowledge base, including SKOS and ontologies modeling structures and relationships. The proposed solution accelerates the knowledge production by crawling and exploiting different kinds of sources (in multiple languages and with several inconsistencies among them). The proposed tool supports the experts in defining relationships among the most recurrent concepts, reducing the time to SKOS production and allowing assisted production. The validity of the produced knowledge base has been assessed by using SPARQL query interface and a precision and recall model. The results have demonstrated better performance with respect to the state of the art. The solution has been developed for Open Space Innovative Mind project, with the aim of creating a portal to allow industries at posing semantic queries to discover potential competences in a large institution such as the University of Florence, in which several distinct domains are associated with its own departments.

In the area of cultural heritage there is a strong push on aggregating content metadata from institutions (such as museums, university, archives, library, foundations, etc.) to make them widely accessible. This action is going to reduce fragmentation, allows aggregation and integrates valuable collections in a unique place. For example, European a (the so called European digital library) collects only metadata, while content files are referred via some URL. These URLs refer to the original content owner and/or to the Content Aggregator, facilitating the collection. That model leaves space to the Content Aggregator to provide additional services on their enriched models. The proposed Content Aggregation model attempts to satisfy specific requirements with a semantic model and tools providing support for executable aggregations such as: play lists, collections, e-learning courses, and media annotations/synchronizations. The produced aggregations may also be provided by mapping semantic concepts to European a. The paper also performs an analysis of semantics models mentioned and of their difficulties including some comments about the adoption of linked open data and media model. The results have been produced in the project ECLAP ICT PSP founded by the European Commission, http://www.eclap.eu.

The content technology needs to attain forms with more intelligence, flexibility and complete features than those being currently on the market or proposed by standards. In this paper, an analysis of the state of the art about intelligent and complex content models is presented. The analysis allowed identifying a number of topics and features which models and formats should evolve according to. The work has been used to extend AXMEDIS content model and format which in turn is grounded on MPEG-21, SMIL, HTML, and other standards. The Extended AXMEDIS format presents a set of new features among them: semantic descriptors, extended annotations, intelligent behavioral and semantic computing capabilities. The newly obtained format has been compared against NewsML which is one of the most widespread formats for news production and distribution. The management of news has some peculiarities such as container, production tools and players, that may take advantage of the intelligent content features and applications. Moreover, news have to be massively processed for ingestion and repurposing, and present relevant requirements on right control. Also these features may be satisfied by AXMEDIS tools. To this end, a comparative analysis of processing and modeling NewsML with AXMEDIS tools and format has been performed and reported to verify the usage. In addition, AXMEDIS format can be profitably used for a range of innovative applications of intelligent content.

Possible solutions to the management of multichannel delivering, production on demand, and containment of sale prices in the digital multimedia content production could be the automating, accelerating and restructuring the production process. The proposed solution provides innovative methods and tools to speed up and optimize content production and distribution based on the GRID technology supported by a specific programming language that allow defining the automatic procedure for content processing, production, adaptation, protection, DRM managing, distribution, etc. This paper describes the GRID architecture of the AXMEDIS Content Processing Area and the language adopted to define algorithms executed into the GRID environment

Despite the relevance of the MPEG-21 standard, little has been done about the modeling of authoring tools and players for the production/consumption of MPEG-21 digital objects. The design and implementation of MPEG-21 tools present several critical points to be solved at the architectural level, so as to ensure security and provide a suitable support and the requested flexibility for manipulating any kind of digital resource, according to the spirit of MPEG-21 standard. This paper presents the AXMEDIS core model and components for MPEG-21 content authoring tools and players. The proposed architecture provides both data manipulation flexibility and a high level of security when digital resources are used. The same architecture can be used to develop any other MPEG-21 DI tools. The architecture presented has been adopted to build authoring and player tools developed for the AXMEDIS IST FP6 R&D European Commission project

The paper on Comments on "An Interval Logic for Real-Time System Specification" presents some remarks on the comparison examples from TILCO and other logics and some slips on the related examples. This paper gives evidence that such issues have no impact on the validity of the TILCO theory of paper and provides some further clarifications about some aspects of the comparison

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.

Temporal logics are able to describe temporal constraints amongst events and actions, as invariance, precedence, periodicity, repeated occurrences, liveness and safety conditions. They are typically used to verify properties in the requirements analysis, in order to describe high level system behaviour and for test case generation. In some cases, temporal logics are used for the specification of real time systems and for their execution. In this paper a model and algorithm to execute specifications in TILCO first order temporal logic are presented. To this end, the TILCO specifications are translated into a model which can be directly, executed by a specific inference engine. An example is also presented.

Among the emerging applications of music scores we can see production and adoption of multimedia digital objects based on music score for distance learning/tuition of music, etc. In these applications, the music notation model has to provide distinct mechanisms for modeling symbolic and visual aspects of music and for defining the relationships among such aspects and in particular between music scores and audio files of real performance. This paper explains the capabilities of WEDELMUSIC regarding the synchronization and execution of music scores synchronous with audio files. The functionality is supported by a free music editor: www.wedelmusic.org. The tool has been developed during the WEDELMUSIC IST Research project funded by the European Commission.

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.

Formal techniques for the specification of real-time systems must be capable of describing a set of relationships expressing the temporal constraints among events and actions: properties of invariance, precedence, periodicity, liveness and safety conditions, etc. This paper describes CTILCO, an extension of TILCO (Temporal Interval Logic with Compositional Operators). CTILCO introduces the communication among components specified in TILCO and allows the adoption of decomposition/composition mechanisms. TILCO has been expressly designed for the specification of real-time systems. CTILCO is based on time intervals and can concisely express temporal constraints with time bounds, such as those needed to specify real-time systems. It can be used to verify the completeness and consistency of specifications, as well as to validate system behavior against its requirements and general properties. CTILCO has been formalized by using the theorem prover Isabelle/HOL. CTILCO specifications satisfying certain properties are executable. CTILCO is defined in terms of theorems and allows the system specification and the formal proof of properties including composition/decomposition with communications. An example of system specification and validation has been also included.

Temporal logics are typically used for the specification of real-time systems since they are capable of describing temporal constraints among events and actions: properties of invariance, precedence, periodicity, repeated occurrences, liveness and safety conditions, etc. This paper describes an evolution of the Temporal Interval Logic called TILCO. TILCO is based on time intervals and can concisely express temporal constraints with time bounds. In this paper, TILCO-X extension of TILCO is presented. TILCO-X proposes two new operators that strongly increase conciseness and readability of specifications to allow describing: the temporal ordering of events without distinction between past and future; and predicates depending on the number of occurrences of events in intervals. TILCO-X is capable to describe specifications by using a lower number of quantifications and of nesting levels between temporal operators. This paper also presents the semantics of TILCO-X and related examples showing the power of the model proposed in terms of conciseness.

System composition/decomposition has to be analyzed in terms of temporal constraints associated with the components' external interface. The analysis is focused on the propagation of temporal constraints along the structural hierarchy, thus showing that in many cases missing temporal constraints can be evaluated on the basis of the temporal constraints known. A set of criteria for the verification of the temporal constraints in a compositional model is presented. A specific graphical notation is proposed. The application of the criteria to a real problem is illustrated by using TROL, an object oriented real time language.

External specification is currently approached by specification languages for describing and analyzing system requirements. The external specification can be defined during the early stages of the system development and can be very useful for: checking the class/system/subsystem requirements; checking the system composition; evaluating costs of reuse; defining validated reference requirements, histories, and traces for the final validation. The paper presents a collection of criteria in order to formally verify the external specification of reactive systems/subsystems. The verification criteria are grounded on the Tempo Reale object-oriented language (TROL) specification model for real-time systems. In TROL, the external specification is expressed in terms of ports and clauses with temporal constraints. The goal of the verification criteria presented is to check the completeness and consistency of the external specification with special attention to temporal constraints. These criteria can be applied to other real-time specification models and have been enforced in the tool object oriented machine state (TOOMS) tool. A practical example illustrates the verification process that embodies these criteria.

Along production pipelines in manufacturing industries, several elaboration phases in which the movement of interpolated axes are present. These activities have to be synchronized with several other simpler activities along the pipeline. Computerized numerical controls for such systems have to be flexible and strongly expandable and reusable since pipelines are frequently reconfigured to realize differently arranged pipelines with different technical requirements. The assessment of such a flexible architecture is presented, on the basis of which the building of flexible distributed controls for pipelines is possible. The architecture has been defined in the ESPRIT HPCN (High Performance Computer Networking) project MUPAAC (Multi Processor Architecture for Automatic Control). MUPAAC architecture and prototype has been assessed in order to identify the most important performance indexes.