João Rocha

Multislice computed tomography in the exclusion of coronary artery disease in pre-surgical valve disease patients

Background—Multislice computed tomography (MSCT) has shown high negative predictive value in ruling out obstructive coronary artery disease. Preliminary studies in patients with valvular heart disease (VHD) have demonstrated the potential of MSCT angiography (CTA) in such patients, precluding need for invasive angiography (XA). However, larger prospectively designed studies, including patients with atrial fibrillation and incorporating dose reduction algorithms, are needed. Methods and Results—To evaluate the clinical utility of 64-slice CT in the preoperative assessment in patients with VHD, we prospectively studied 452 consecutive patients undergoing routine cardiac catheterization for eligibility. Two hundred thirty-seven patients underwent both MSCT and XA. Segment-based, vessel-based, and patient-based agreement between CTA and XA was estimated assuming that “nonevaluable” segments were positive for significant coronary stenosis. In a patient-based analysis, sensitivity, specificity, positive predictive value, and negative predictive values of CTA were 95%, 89%, 66%, and 99%, respectively; in vessel-based analysis, 90%, 92%, 48%, and 99%, respectively; and in segment-based analysis, 89%, 97%, 38%, and 100%, respectively. No significant differences were found between patients with or without atrial fibrillation. A CAC value of 390 was the best cutoff for the identification of patients with positive or inconclusive CTA (which would not be exempted from XA in the clinical setting). Conclusions—In the preoperative assessment of patients with predominant VHD, the diagnostic accuracy of 64-slice CTA for ruling out the presence of significant coronary artery disease is very good even when including patients with irregular heart rhythm. Using this approach, CAC quantification before CTA can be successfully used to identify patients who should be referred directly to XA, sparing unnecessary exposure to radiation.

Semantic Web complex ontology mapping

Ontology mapping is the process whereby two ontologies are semantically related at conceptual level and the source ontology instances are transformed into target ontology entities according to those semantic relations. Ontology mapping faces new challenges in the context of semantic Web, especially concerning heterogeneity, dynamics, distribution and limitations on representation technology. We introduce a new methodology and transformation process based on the notion of service, which represents system transformation capabilities. MAFRA toolkit is a specific implementation of MAFRA-mapping framework, where these new methodology and transformation process are being validated. MAFRA toolkit is being applied in the European project Harmonise, which aims to provide solutions for (semi) automatic interoperability between major operators in tourism e-business. MAFRA plays a major role in the specification, representation and reconciliation phases of the semantic mapping within the scope of the Harmonise technology.

Task planning for flexible and agile manufacturing systems

This paper deals with task and execution planning for manufacturing systems. We describe a system named TPMS (task planning for manufacturing systems). The final goal of this system is to automatically generate programs or sets of commands for robots, AGVs, numerical control machines and other components of the system without the need of spending much time programming the flexible manufacturing system (FMS) components. The sequence of operations to be handled by the manufacturing system depends on the constraints for the task. Three types of constraints are defined and explained: processing constraints, feasibility constraints and geometric constraints. The symbolic plan for the task is represented in the form of a precedence graph. High level operations can be converted into programs or sets of instructions to control the manufacturing systems equipment. The main contributions of TPMS are the following. To put together symbolic planning and execution planning; it is being developed to work for complete manufacturing systems (and not for controlling only one robot); different industrial operations (assembly, welding, drilling, ...) can be considered at the same time.<<ETX>>

Process planning using a genetic algorithm approach

This paper presents a system for computer aided process planning (CAPP), using a precedence graph representation of the operations and their restrictions. Description of machine and tool selection is described, as well as the operation sequencing. A genetic algorithm is used to generate the sequence of operations and to select the machine and tools that minimize some criteria (machining time).

E-Business Interoperability Through Ontology Semantic Mapping

With the advent of Semantic Web, knowledge-based interoperability in VE faces a new technological shift, in which ontologies and semantic web technologies plays a major role. Exploiting the explicit semantic description of the domain of discourse allows reasoning and automatically acquiring semantic relations between two different domains of discourses. Such semantic relations would be further applied in converting data between such domains. This process is named Ontology Mapping. The MAFRA—Mapping FRAmework cover all the phases of the process, including analysis, specification, representation, execution and evolution. The execution strategy and methodology are the focus of this paper. The MAFRA Toolkit is being applied in the European project Harmonise, which aims to provide solutions for (semi-) automatic interoperability between major operators in e-tourism.

On the complexity of precedence graphs for assembly and task planning

This paper deals with a complete and correct method to compute how many plans exist for an assembly or processing task. Planning is a NP-hard problem and then, in some situations, the application of time consuming search methods must be avoided. However, up to now the computation of the exact number of alternative plans for any situation was not reported elsewhere. Notice that the complexity of the problem does not depend on the number of involved operations, components or parts. The complexity of the problem depends on the topology of the precedences between operations. With the method presented in this paper, it will be easy to decide the search method to use, since we know how many possible plans could exist before applying the search method.

Plan representation and generation for manufacturing tasks

This paper deals with a system named TPMS (Task Planning for Manufacturing Systems). The final goal of this system is to automatically generate programs or sets of commands for robots, AGVs, numerical control machines and other components of the system without the need of spending much time programming the FMS components. In this paper the authors describe how to automatically generate a high level plan for the task. The sequence of operations to be handled by the manufacturing system depends on the constraints for the task. Three types of constraints are defined and explained: processing constraints; feasibility constraints and geometric constraints. The symbolic plan for the task is represented in the form of a precedence graph. The main contributions of TPMS are the following ones: to put together symbolic planning and execution planning; it is being developed to work for complete manufacturing systems (and not for controlling only one robot); different industrial operations can be considered at the same time.

Generating and converting plans for intelligent manufacturing systems

This paper describes a system named TPMS (Task Planning for Manufacturing Systems). The final goal of this system is to automatically generate programs or sets of commands for robots, AGVs, numerical control machines and other components of the system without the need of spending much time programming the flexible manufacturing system (FMS) components. The sequence of operations to be handled by the manufacturing system depends on the constraints for the task. Three types of constraints are defined and explained: processing constraints; feasibility constraints and geometric constraints. The symbolic plan for the task is represented in the form of a precedence graph. High level operations can be converted into programs or sets of instructions to control the manufacturing systems equipment. The main contributions of TPMS are the following: to put together symbolic planning and execution planning; it is being developed to work for complete manufacturing systems (and not for controlling only one robot); different industrial operations (assembly, welding, drilling, etc.) can be considered at the same time.<<ETX>>

Multidimensional service-oriented ontology mapping

Ontology mapping is the process whereby semantic relations are defined between two ontologies at conceptual level, which in turn are applied at data level transforming source ontology instances into target ontology instances. This paper focuses on the formalisation, representation and automatic specification of semantic relations between two ontologies. The described approach grounds on the notion of service, which represents not only the transformation capabilities of the system, but also the expertise in the manipulation of semantic relations. The main contributions of this paper are the formalisation of the ontology mapping process and the specification of the multidimensional service-oriented architecture.

Representing and generating operation sequences for manufacturing tasks

This paper deals with a system called TPMS (Task Planning for Manufacturing Systems). The main aim of this system is to automatically generate programs or sets of commands for robots, AGV, numerical control machines, etc, without spending much time programming the flexible manufacturing system components. The sequence of operations to be handled by the manufacturing system depends on the constraints for the task. The symbolic plan for the task is represented in the form of a precedence graph. The main contributions are the following ones: to link symbolic and execution planning; the referred aims at working for complete manufacturing systems; different industrial operations can be considered at the same time.