Radiology Service Bus: Interoperabilidade semântica para Radiologia

A integração de sistemas é um tema sempre actual na temática das tecnologias de informação. Desde há muito tempo que as grandes empresas identificaram a necessidade de integrar dados de diferentes sistemas, criando mais valor para os seus negócios. Alguns sectores da indústria estão claramente mais avançados do que outros no que diz respeito à integração de sistemas. Alguns factores, como a concorrência e competitividade mais agressiva em alguns mercados, foram os catalisadores desses avanços tecnológicos. A indústria da saúde não foi, infelizmente, um dos sectores onde se registaram grandes avanços na integração de sistemas. Foi, no entanto, onde se registou uma explosão de normas e protocolos que suportam as diversas disciplinas da medicina, como por ex, a Radiologia. Essas normas e protocolos permitiram dotar a medicina de meios mais rigorosos de produzir diagnósticos e encontrar curas para as mais diversas patologias. Existem muitos produtos que adoptam estas normas. As organizações foram, progressivamente, adquirindo esses produtos mas sem grande preocupação da eventual necessidade da integração. A disciplina da Radiologia é uma das disciplinas onde se verifica, ainda hoje, uma enorme diversidade de equipamentos e sistemas de informação mas onde se encontra desafios consideráveis no que diz respeito à integração. Foram esses desafios que despoletaram o interesse de investigação e cujos resultados se partilham nesta dissertação.

A holistic approach to model-based testing of Web service compositions

The behavior of composed Web services depends on the results of the invoked services; unexpected behavior of one of the invoked services can threat the correct execution of an entire composition. This paper proposes an event-based approach to black-box testing of Web service compositions based on event sequence graphs, which are extended by facilities to deal not only with service behavior under regular circumstances (i.e., where cooperating services are working as expected) but also with their behavior in undesirable situations (i.e., where cooperating services are not working as expected). Furthermore, the approach can be used independently of artifacts (e.g., Business Process Execution Language) or type of composition (orchestration/choreography). A large case study, based on a commercial Web application, demonstrates the feasibility of the approach and analyzes its characteristics. Test generation and execution are supported by dedicated tools. Especially, the use of an enterprise service bus for test execution is noteworthy and differs from other approaches. The results of the case study encourage to suggest that the new approach has the power to detect faults systematically, performing properly even with complex and large compositions. Copyright © 2012 John Wiley & Sons, Ltd.

Open standards-based system integration for asset management decision support

Over the last decade, system integration has grown in popularity as it allows organisations to streamline business processes. Traditionally, system integration has been conducted through point-to-point solutions – as a new integration scenario requirement arises, a custom solution is built between the relevant systems. Bus-based solutions are now preferred, whereby all systems communicate via an intermediary system such as an enterprise service bus, using a common data exchange model. This research investigates the use of a common data exchange model based on open standards, specifically MIMOSA OSA-EAI, for asset management system integration. A case study is conducted that involves the integration of processes between a SCADA, maintenance decision support and work management system. A diverse number of software platforms are employed in developing the final solution, all tied together through MIMOSA OSA-EAI-based XML web services. The lessons learned from the exercise are presented throughout the paper.

A novel context ontology to facilitate interoperation of semantic services in environments with wearable devices

The LifeWear-Mobilized Lifestyle with Wearables (Lifewear) project attempts to create Ambient Intelligence (AmI) ecosystems by composing personalized services based on the user information, environmental conditions and reasoning outputs. Two of the most important benefits over traditional environments are 1) take advantage of wearable devices to get user information in a nonintrusive way and 2) integrate this information with other intelligent services and environmental sensors. This paper proposes a new ontology composed by the integration of users and services information, for semantically representing this information. Using an Enterprise Service Bus, this ontology is integrated in a semantic middleware to provide context-aware personalized and semantically annotated services, with discovery, composition and orchestration tasks. We show how these services support a real scenario proposed in the Lifewear project.

An Internet of Things approach for managing smart services provided by wearable devices.

The Internet of Things (IoT) is growing at a fast pace with new devices getting connected all the time. A new emerging group of these devices are the wearable devices, and Wireless Sensor Networks are a good way to integrate them in the IoT concept and bring new experiences to the daily life activities. In this paper we present an everyday life application involving a WSN as the base of a novel context-awareness sports scenario where physiological parameters are measured and sent to the WSN by wearable devices. Applications with several hardware components introduce the problem of heterogeneity in the network. In order to integrate different hardware platforms and to introduce a service-oriented semantic middleware solution into a single application, we propose the use of an Enterprise Service Bus (ESB) as a bridge for guaranteeing interoperability and integration of the different environments, thus introducing a semantic added value needed in the world of IoT-based systems. This approach places all the data acquired (e.g., via Internet data access) at application developers disposal, opening the system to new user applications. The user can then access the data through a wide variety of devices (smartphones, tablets, computers) and Operating Systems (Android, iOS, Windows, Linux, etc.).

Evaluación del dispositivo Raspberry Pi como elemento de despliegue de servicios en el marco de las Smart Grids

La tendencia actual de las redes de telecomunicaciones conduce a pensar en un futuro basado en el concepto emergente de las Smart Cities¸ que tienen como objetivo el desarrollo urbano basado en un modelo de sostenibilidad que responda a las necesidades crecientes de las ciudades. Dentro de las Smart Cities podemos incluir el concepto de Smart Grid, el cual está referido a sistemas de administración y producción de energía eficientes, que permitan un sistema energético sostenible, y que den cabida a las fuentes de energía renovables. Sistemas de este tipo se muestran a los usuarios como un conjunto de servicios con los que interactuar sin ser tan sólo un mero cliente, sino un agente más del entorno energético. Por otro lado, los sistemas de software distribuidos son cada vez más comunes en una infraestructura de telecomunicaciones cada vez más extensa y con más capacidades. Dentro de este ámbito tecnológico, las arquitecturas orientadas a servicios han crecido exponencialmente sobre todo en el sector empresarial. Con sistemas basados en estas arquitecturas, se pueden ofrecer a empresas y usuarios sistemas software basados en el concepto de servicio. Con la progresión del hardware actual, la miniaturización de los equipos es cada vez mayor, sin renunciar por ello a la potencia que podemos encontrar en sistemas de mayor tamaño. Un ejemplo es el dispositivo Raspberry Pi, que contiene un ordenador plenamente funcional contenido en el tamaño de una cajetilla de tabaco, y con un coste muy reducido. En este proyecto se pretenden aunar los tres conceptos expuestos. De esta forma, se busca utilizar el dispositivo Raspberry Pi como elemento de despliegue integrado en una arquitectura de Smart Grid orientada a servicios. En los trabajos realizados se ha utilizado la propuesta definida por el proyecto de I+D europeo e-GOTHAM, con cuya infraestructura se ha tenido ocasión de realizar diferentes pruebas de las descritas en esta memoria. Aunque esta arquitectura está orientada a la creación de una Smart Grid, lo experimentado en este PFG podría encajar en otro tipo de aplicaciones. Dentro del estudio sobre las soluciones software actuales, se ha trabajado en la evaluación de la posibilidad de instalar un Enterprise Service Bus en el Raspberry Pi y en la optimización de la citada instalación. Una vez conseguida una instalación operativa, se ha desarrollado un controlador de un dispositivo físico (sensor/actuador), denominado Dispositivo Lógico, a modo de prueba de la viabilidad del uso del Raspberry Pi para actuar como elemento en el que instalar aplicaciones en entornos de Smart Grid o Smart Home. El éxito logrado con esta experimentación refuerza la idea de considerar al Raspberry Pi, como un importante elemento a tener en cuenta para el despliegue de servicios de Smart Cities o incluso en otros ámbitos tecnológicos. ABSTRACT. The current trend of telecommunication networks lead to think in a future based on the emerging concept of Smart Cities, whose objective is to ensure the urban development based on a sustainable model to respond the new necessities of the cities. Within the Smart cites we can include the concept of Smart Grid, which is based on management systems and efficient energy production, allowing a sustainable energy producing system, and that includes renewable energy sources. Systems of this type are shown to users as a set of services that allow users to interact with the system not only as a single customer, but also as other energy environment agent. Furthermore, distributed software systems are increasingly common in a telecommunications infrastructure more extensive and with more capabilities. Within this area of technology, service-oriented architectures have grown exponentially especially in the business sector. With systems based on these architectures, can be offered to businesses and users software systems based on the concept of service. With the progression of the actual hardware, the miniaturization of computers is increasing, without sacrificing the power of larger systems. An example is the Raspberry Pi, which contains a fully functional computer contained in the size of a pack of cigarettes, and with a very low cost. This PFG (Proyecto Fin de Grado) tries to combine the three concepts presented. Thus, it is intended to use the Raspberry Pi device as a deployment element integrated into a service oriented Smart Grid architecture. In this PFG, the one proposed in the European R&D e-GOTHAM project has been observed. In addition several tests described herein have been carried out using the infrastructure of that project. Although this architecture is oriented to the creation of a Smart Grid, the experiences reported in this document could fit into other applications. Within the study on current software solutions, it have been working on assessing the possibility of installing an Enterprise Service Bus in the Raspberry Pi and optimizing that facility. Having achieved an operating installation, it has been developed a driver for a physical device (sensor / actuator), called logical device, for testing the feasibility of using the Raspberry Pi to act as an element in which to install applications in Smart Grid and Smart Home Environments. The success of this experiment reinforces the idea of considering the Raspberry Pi as an important element to take into account in the deployment of Smart Cities services or even in other technological fields.

An E-government Interoperability Platform Supporting Personal Data Protection Regulations

Public agencies are increasingly required to collaborate with each other in order to provide high-quality e-government services. This collaboration is usually based on the service-oriented approach and supported by interoperability platforms. Such platforms are specialized middleware-based infrastructures enabling the provision, discovery and invocation of interoperable software services. In turn, given that personal data handled by governments are often very sensitive, most governments have developed some sort of legislation focusing on data protection. This paper proposes solutions for monitoring and enforcing data protection laws within an E-government Interoperability Platform. In particular, the proposal addresses requirements posed by the Uruguayan Data Protection Law and the Uruguayan E-government Platform, although it can also be applied in similar scenarios. The solutions are based on well-known integration mechanisms (e.g. Enterprise Service Bus) as well as recognized security standards (e.g. eXtensible Access Control Markup Language) and were completely prototyped leveraging the SwitchYard ESB product.

Bus and car travel time on urban networks : integrating Bluetooth and bus vehicle identification data

Travel time in an important transport performance indicator. Different modes of transport (buses and cars) have different mechanical and operational characteristics, resulting in significantly different travel behaviours and complexities in multimodal travel time estimation on urban networks. This paper explores the relationship between bus and car travel time on urban networks by utilising the empirical Bluetooth and Bus Vehicle Identification data from Brisbane. The technologies and issues behind the two datasets are studied. After cleaning the data to remove outliers, the relationship between not-in-service bus and car travel time and the relationship between in-service bus and car travel time are discussed. The travel time estimation models reveal that the not-in-service bus travel time are similar to the car travel time and the in-service bus travel time could be used to estimate car travel time during off-peak hours

Empirical modelling of the relationship between bus and car speeds on signalised urban networks

Vehicle speed is an important attribute for the utility of a transport mode. The speed relationship between multiple modes of transport is of interest to the traffic planners and operators. This paper quantifies the relationship between bus speed and average car speed by integrating Bluetooth data and Transit Signal Priority data from the urban network in Brisbane, Australia. The method proposed in this paper is the first of its kind to relate bus speed and average car speed by integrating multi-source traffic data in a corridor-based method. Three transferable regression models relating not-in-service bus; in-service bus during peak; and in-service bus during off peak periods with average car are proposed. The models are cross-validated and the interrelationships are significant

How transit route passenger load and distance can together influence quality of service

This paper investigates: - correlation between transit route passenger loading and travel distance - its implications on quality of service (QoS) and resource productivity. It uses Automatic Fare Collection (AFC) data across a weekday on a premium bus line in Brisbane, Australia. A composite load-distance factor is proposed as a new measure for profiling transit route on-board passenger comfort QoS. Understanding these measures and their correlation is important for planning, design, and operational activities.

How transit route passenger load and distance can together influence quality of service

This paper investigates quality of service and resource productivity implications of transit route passenger loading and travel distance. Weekday Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia, is used to investigate correlation between load factor and distance factor. Relationships between boardings and transit work indicate that distance factor generally increases with load factor. Time series analysis is then presented by examining each direction on an hour by hour basis. Inbound correlation is medium to strong across the entire span of service and strong for daytime services up to 19:30, while outbound correlation is strong across the entire span. Passengers tend to be making longer distance, peak direction commuter trips under the least comfortable conditions under stretched peak schedules than off-peak. Therefore productivity gains may be possible by adjusting fleet utilization during off-peak times. Weekday profiles by direction are established for a composite load-distance factor. A threshold corresponding to standing passengers on the Maximum Load Segment reveals that on-board loading and travel distance combined are more severe during the morning inbound peak than evening outbound peak, although the sharpness of the former suggests that encouraging shoulder peak travel during the morning would be more effective than evening peak. Further research suggested includes: consideration of travel duration factor, relating noise within hour to Peak Hour Factor, profiling load-distance factor across a range of case studies, and relating load-distance factor threshold to line length.

Modeling Bus Rapid Transit station bus queuing for Bus Rapid Transit station bus operation analysis

Stations on Bus Rapid Transit (BRT) lines ordinarily control line capacity because they act as bottlenecks. At stations with passing lanes, congestion may occur when buses maneuvering into and out of the platform stopping lane interfere with bus flow, or when a queue of buses forms upstream of the station blocking inflow. We contend that, as bus inflow to the station area approaches capacity, queuing will become excessive in a manner similar to operation of a minor movement on an unsignalized intersection. This analogy is used to treat BRT station operation and to analyze the relationship between station queuing and capacity. In the first of three stages, we conducted microscopic simulation modeling to study and analyze operating characteristics of the station under near steady state conditions through output variables of capacity, degree of saturation and queuing. A mathematical model was then developed to estimate the relationship between average queue and degree of saturation and calibrated for a specified range of controlled scenarios of mean and coefficient of variation of dwell time. Finally, simulation results were calibrated and validated.

Empirical modelling of the relationship between bus and car speeds on signalised urban networks

Vehicle speed is an important attribute for analysing the utility of a transport mode. The speed relationship between multiple modes of transport is of interest to traffic planners and operators. This paper quantifies the relationship between bus speed and average car speed by integrating Bluetooth data and Transit Signal Priority data from the urban network in Brisbane, Australia. The method proposed in this paper is the first of its kind to relate bus speed and average car speed by integrating multi-source traffic data in a corridor-based method. Three transferable regression models relating not-in-service bus, in-service bus during peak periods, and in-service bus during off-peak periods with average car speed are proposed. The models are cross-validated and the interrelationships are significant.

A Hub System for Cloud-Computing Based Business-Collaboration: Automating Ontology-Enabled Electronic Business-Service Discovery

The management and coordination of business-process collaboration experiences changes because of globalization, specialization, and innovation. Service-oriented computing (SOC) is a means towards businessprocess automation and recently, many industry standards emerged to become part of the service-oriented architecture (SOA) stack. In a globalized world, organizations face new challenges for setting up and carrying out collaborations in semi-automating ecosystems for business services. For being efficient and effective, many companies express their services electronically in what we term business-process as a service (BPaaS). Companies then source BPaaS on the fly from third parties if they are not able to create all service-value inhouse because of reasons such as lack of reasoures, lack of know-how, cost- and time-reduction needs. Thus, a need emerges for BPaaS-HUBs that not only store service offers and requests together with information about their issuing organizations and assigned owners, but that also allow an evaluation of trust and reputation in an anonymized electronic service marketplace. In this paper, we analyze the requirements, design architecture and system behavior of such a BPaaS-HUB to enable a fast setup and enactment of business-process collaboration. Moving into a cloud-computing setting, the results of this paper allow system designers to quickly evaluate which services they need for instantiationg the BPaaS-HUB architecture. Furthermore, the results also show what the protocol of a backbone service bus is that allows a communication between services that implement the BPaaS-HUB. Finally, the paper analyzes where an instantiation must assign additional computing resources vor the avoidance of performance bottlenecks.

Real-Time and Data-Driven Operation Optimization and Knowledge Discovery for an Enterprise Information System

An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.