NOViSE: a virtual natural orifice transluminal endoscopic surgery simulator

Purpose: Natural Orifice Transluminal Endoscopic Surgery (NOTES) is a novel technique in minimally invasive surgery whereby a flexible endoscope is inserted via a natural orifice to gain access to the abdominal cavity, leaving no external scars. This innovative use of flexible endoscopy creates many new challenges and is associated with a steep learning curve for clinicians. Methods: We developed NOViSE - the first force-feedback enabled virtual reality simulator for NOTES training supporting a flexible endoscope. The haptic device is custom built and the behaviour of the virtual flexible endoscope is based on an established theoretical framework – the Cosserat Theory of Elastic Rods. Results: We present the application of NOViSE to the simulation of a hybrid trans-gastric cholecystectomy procedure. Preliminary results of face, content and construct validation have previously shown that NOViSE delivers the required level of realism for training of endoscopic manipulation skills specific to NOTES Conclusions: VR simulation of NOTES procedures can contribute to surgical training and improve the educational experience without putting patients at risk, raising ethical issues or requiring expensive animal or cadaver facilities. In the context of an experimental technique, NOViSE could potentially facilitate NOTES development and contribute to its wider use by keeping practitioners up to date with this novel surgical technique. NOViSE is a first prototype and the initial results indicate that it provides promising foundations for further development

An empirical study evaluating depth of inheritance on the maintainability of object-oriented software

This empirical research was undertaken as part of a multi-method programme of research to investigate unsupported claims made of object-oriented technology. A series of subject-based laboratory experiments, including an internal replication, tested the effect of inheritance depth on the maintainability of object-oriented software. Subjects were timed performing identical maintenance tasks on object-oriented software with a hierarchy of three levels of inheritance depth and equivalent object-based software with no inheritance. This was then replicated with more experienced subjects. In a second experiment of similar design, subjects were timed performing identical maintenance tasks on object-oriented software with a hierarchy of five levels of inheritance depth and the equivalent object-based software. The collected data showed that subjects maintaining object-oriented software with three levels of inheritance depth performed the maintenance tasks significantly quicker than those maintaining equivalent object-based software with no inheritance. In contrast, subjects maintaining the object-oriented software with five levels of inheritance depth took longer, on average, than the subjects maintaining the equivalent object-based software (although statistical significance was not obtained). Subjects' source code solutions and debriefing questionnaires provided some evidence suggesting subjects began to experience diffculties with the deeper inheritance hierarchy. It is not at all obvious that object-oriented software is going to be more maintainable in the long run. These findings are sufficiently important that attempts to verify the results should be made by independent researchers

Boosting computational power through spatial multiplexing in quantum reservoir computing

Quantum reservoir computing provides a framework for exploiting the natural dynamics of quantum systems as a computational resource. It can implement real-time signal processing and solve temporal machine learning problems in general, which requires memory and nonlinear mapping of the recent input stream using the quantum dynamics in computational supremacy region, where the classical simulation of the system is intractable. A nuclear magnetic resonance spin-ensemble system is one of the realistic candidates for such physical implementations, which is currently available in laboratories. In this paper, considering these realistic experimental constraints for implementing the framework, we introduce a scheme, which we call a spatial multiplexing technique, to effectively boost the computational power of the platform. This technique exploits disjoint dynamics, which originate from multiple different quantum systems driven by common input streams in parallel. Accordingly, unlike designing a single large quantum system to increase the number of qubits for computational nodes, it is possible to prepare a huge number of qubits from multiple but small quantum systems, which are operationally easy to handle in laboratory experiments. We numerically demonstrate the effectiveness of the technique using several benchmark tasks and quantitatively investigate its specifications, range of validity, and limitations in detail.Comment: 15 page

Personality traits and beliefs about peers\u2019 on-road behaviors as predictors of adolescents\u2019 moped-riding profiles.

Several efforts aimed at discriminating between different degrees of on-road risky attitudes have been devoted to the identification of personality profiles among young drivers. However, the results are often inconsistent because of the limits of selfreport measures. To overcome these limits, we tried to identify different profiles based on our study participants\u2019 driving performances in a virtual environment and to look for psychological predictors of inclusion in one of three profiles. One-hundred and fourteen inexperienced adolescents were involved in this study, which included two experimental sessions. During the first, before riding along five virtual courses on a moped simulator, participants\u2019 sensation seeking, locus of control, aggressiveness and beliefs about their peers\u2019 on-road behaviors were measured by means of self-report tools. During the second session, the participants drove the simulator along six courses that were different from those faced in the first session. A cluster analysis was run on a wide number of indexes extracted from the participants\u2019 performances to detect different riding profiles. Three profiles emerged (Imprudent, Prudent and Insecure), with specific riding patterns. The profiles also differed in terms of riding safety, assessed by means of the scores automatically given by the simulator to the participants\u2019 performances. Reporting an external locus of control, underestimating peers\u2019 on-road risky behaviors and showing less concern for fate among the possible causes of crashes are predictors that increase the risk of being included in the Imprudent profile. Low levels of dangerous thrill seeking predict inclusion in the Prudent profile, whereas high rates of self-reported anger play a role in discriminating the Insecure riders from the other profiles. The study indicates that it is possible to identify riding profiles with different degrees of on-road safety among inexperienced adolescents by means of simulated road environments. Moreover, inclusion in these profiles is predicted by different patterns of personality variables and beliefs. Further research is needed to verify the validity of these conclusions in real road conditions

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse