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Gastric bypass has become the gold standard procedure of weight-loss surgery, and the minimally invasive approach improves its outcomes. Laparoscopic gastric bypass, however, remains a technically demanding procedure and is associated with a steep learning curve. This learning curve is associated with longer operative times and increased complication rates. The robotic technology has brought some significant advantages in the field of minimally invasive bariatric surgery by improving dissection and suturing abilities in difficult-to-reach areas of the abdomen. Growing evidence suggests that these characteristics may result in improved clinical outcomes. These advantages, combined with the teaching facilities of the robot such as simulation and tele-mentoring, may also improve and shorten the learning process of minimally invasive gastric bypass. After describing the learning curve of laparoscopic gastric bypass, the present chapter explores the potential benefits of the robotic technology and its impact on the learning process.

Real-time system design involves proving the schedulability of a set of tasks with hard timing and other constraints that should run on one or several cores. When those requirements are known at design time, it is possible to compute a fixed scheduling of tasks before deployment. This approach avoids the overhead induced by an online scheduler and allows the designer to verify the schedulability of the taskset design under normal and degraded conditions, such as core failures. In this context, we propose to solve the schedulability problem as a state space exploration problem. We represent the schedulings as partial functions that map each task to a core and a point in time. Partial functions can be efficiently encoded using a new variant of decision diagrams, called Map-Family Decision Diagrams (MFDDs). Our setting allows first to create the MFDD of all possible schedulings and then apply homomorphic operations directly on it, in order to obtain the schedulings that respect the constraints of the taskset.

The study of concurrent and parallel systems has been a challenging research domain within cyberphysical systems community. This chapter provides a pragmatic introduction to the creation and analysis of such system models using the popular Petri nets formalism. Petri nets is a formalism that convinces through its simplicity and applicability.We offer an overview of the most important Petri nets concepts, analysis techniques and model checking approaches. Finally, we show the use of so-called High-level Petri nets for the representation of complex data structures and functionality and present a novel research approach that allows the use of Petri nets inside Functional Mock-up Units and cyber-physical system models.

Representing the context of triples and reasoning on contextualized triples is an open problem in the semantic web. In this paper, we present OWLc: a contextual two-dimensional web ontology language. Using the first dimension, we can define contexts-dependent classes, properties, and axioms and using the second dimension, we can express knowledge about contexts which we consider formal objects, as proposed by McCarthy [17]. Moreover, we describe a contextual extension of the OWL entailment rules, and we present a new set of rules for reasoning on contexts. We demonstrate the modeling strength and reasoning capabilities of OWLc with a practical scenario from the digital humanity domain. We chose the FDS project in virtue of its inherent contextual nature, as well as its notable complexity which allow us to highlight many issues connected with contextual knowledge representation and reasoning.

At the dawn of the 21st century, medical robotics were introduced into clinical practice. This chapter outlines the development of robotics in the context of advancements in transanal surgery. It details how the field of robotic TAMIS was developed and reviews progress to date with this technique, including the application of transanal robotics for taTME. Robotic TAMIS is poised to evolve dramatically as new technology, automization, and NOTES-based, single-port robotic platforms emerge from concept to operating theater.

Gain of experience by learning only in the operating room is no longer relevant. Like surgery itself, training had to evolve and adapt to new challenges. Acquisition of knowledge and the preparation of the trainee is an active phase. Virtual reality, box trainers, animal and cadaveric models are means to reach an adequate skill level and be able to manage situations in patient with sufficient safety. Surgical technique must finally be fully acquired with during the interventions with an expert surgeon who will be able to make the necessary corrections and feedbacks. A clear training curriculum must be implemented in each colorectal surgery program. It should be used to validate the transition to a higher step and standardize the surgical practice.

This paper introduces mcc4mcc, the Model Checker Collection for the Model Checking Contest, a tool that wraps multiple model checking solutions, and applies the most appropriate one based on the characteristics of the model it is given. It leverages machine learning algorithms to carry out this selection, based on the results gathered from the 2017 edition of the Model Checking Contest, an annual event in which multiple tools compete to verify different properties on a large variety of models. Our approach brings two important contributions. First, our tool offers the opportunity to further investigate on the relation between model characteristics and verification techniques. Second, it lays out the groundwork for a unified way to distribute model checking software using virtual containers.

This article presents CREST, a novel domain-specific language for the modelling of cyber-physical systems. CREST is designed for the simple and clear modelling, simulation and verification of small-scale systems such as home and office automation, smart gardening systems and similar. The language is designed to model the flow of resources throughout the system. It features synchronous system evolution and reactive behaviour. CREST's formal semantics allow real-valued time advances and the modelling of timed system evolution. The continuous time concept permits the precise simulation of future system behaviour by automatically calculating next transition times. We present CREST in a practical manner, and elaborate on the Python-based DSL implementation and simulator.

Over the last decade code-based test case generation techniques such as combinatorial testing or dynamic symbolic execution have seen growing research popularity. Most algorithms and tool implementations are based on finding assignments for input parameter values in order to maximise the execution branch coverage. In this paper we first present ITEC, a tool for automated test case generation in CTRL, as well as initial results of test cases executions on one of CERN’s SCADA frameworks. Our tool relies on Microsoft’s Pex for its code exploration. For the purpose of using this existing test generation tool, we have to translate the proprietary CTRL code into C#, one of Pex’s operating languages. Our main contribution lies in detailing a formal foundation for this step through source code decomposition and anonymization. We then propose a quality measure that is used to determine our confidence into the translation and the generated test cases.

Over the past few years, numerous real-time and embedded systems have been adopting multi-core architectures for either better performances, or energy efficiency. For the case of real-time applications, where tasks can have critical deadlines, it is desirable to ensure the schedulability of the application statically, taking into account the possible software and hardware failures. While a lot of effort have been made to handle software misbehaviours, resilience to hardware failures has often been overlooked.

The risk of biliary injury during cholecystectomy has increased with the introduction of laparoscopy, with even greater concerns using the single-site approach. On the other hand, the development of a new robotic single-site platform was seen as a potential technical help. In addition, the introduction of real-time near-infrared fluorescent cholangiography during robotic single-site cholecystectomy can also help in assessing the biliary anatomy and might reduce the risk of biliary injury. Moreover, this technology could shorten the operative time in selected patients and might be useful for the development of augmented reality and image-guided surgery in the future.