Arthemis: annotation software in an integrated capturing and analysis system for colonoscopy

Colonoscopy is an endoscopic technique that allows physicians to inspect the inside of the human colon. During a colonoscopic procedure, a tiny video camera at the tip of the endoscope generates a video signal of the internal mucosa of the colon. In current practice, the entire colonoscopic procedure is not routinely captured. Software tools providing easy access to important contents of videos that are digitally captured during colonoscopy are not available. Hence, it is very time consuming to review an entire video, locate important contents, annotate them, and extract the annotated contents for research, teaching, and training purposes. Arthemis, a software application, was developed to facilitate this process. For convenient data sharing, Arthemis allows annotation according to the European Gastrointestinal Society for Endoscopy (ESGE) Minimal Standard Terminology (MST), an internationally accepted standard for digestive endoscopy. Arthemis is part of our integrated capturing and content analysis system for colonoscopy called Endoscopic Multimedia Information System (EMIS). This paper presents Arthemis as a component of EMIS, the design and implementation of Arthemis, and key lessons learned from the development process.     

Property Testing of Regular Tree Languages

We consider the edit distance with moves on the class of words and the class of ordered trees. We first exhibit a simple tester for the class of regular languages on words and generalize it to the class of ranked and unranked regular trees. We also show that this distance problem is -complete on ordered trees. A preliminary version of this paper appeared in Proceedings of 31st International Colloquium on Automata, Languages and Programming, volume 3142 of Lecture Notes in Computer Science, pages 932–944, Springer, 2005. Work supported by ACI Sécurité Informatique: VERA of the French Ministry of research.     

An expert system for managing medical appropriateness criteria based on computer algebra techniques

This article presents the development of an expert system for managing medical appropriateness criteria together with an outline of its theoretical foundations. Techniques borrowed from computer algebra (Gröbner bases) are applied to this field of medicine.

The steps of the expert system construction process are as follows. First, the knowledge provided in table format by experts in coronary diseases is translated into a set of production rules of a rule-based expert system (RBES). Kleene's three-valued logic augmented with modal operators is chosen in order to manage uncertainty.     

A Framework for Integrating Non-Functional Requirements into Conceptual Models

The development of complex information systems calls for conceptual models that describe aspects beyond entities and activities. In particular, recent research has pointed out that conceptual models need to model goals, in order to capture the intentions which underlie complex situations within an organisational context. This paper focuses on one class of goals, namely non-functional requirements (NFR), which need to be captured and analysed from the very early phases of the software development process. The paper presents a framework for integrating NFRs into the ER and OO models. This framework has been validated by two case studies, one of which is very large. The results of the case studies suggest that goal modelling during early phases can lead to a more productive and complete modelling activity.       

A semiotic engineering approach to user interface design

Designing software involves good perception, good reasoning, and a talent to express oneself effectively through programming and interactive languages. Semiotic theories can help HCI designers increase their power to perceive, reason and communicate. By presenting some of the results we have reached with semiotic engineering over the last few years, we suggest that the main contributions of semiotic theory in supporting HCI design are: to provide designers with new perceptions on the process and product of HCI design; to bind together all the stages of software development and use, giving them a unique homogeneous treatment; and to pose innovative questions that extend the frontiers of HCI investigations.     

Making Workflow Change Acceptable

Virtual professional communities are supported by network information systems composed from standard Internet tools. To satisfy the interests of all community members, a user-driven approach to requirements engineering is proposed that produces not only meaningful but also acceptable specifications. This approach is especially suited for workflow systems that support partially structured, evolving work processes. To ensure the acceptability, social norms must guide the specification process. The RENISYS specification method is introduced, which facilitates this process using composition norms as formal representations of social norms. Conceptual graph theory is used to represent four categories of knowledge definitions: type definitions, state definitions, action norms and composition norms. It is shown how the composition norms guide the legitimate user-driven specification process by analysing a case on the development of an electronic law journal.     

LARS: A learning algorithm for rewriting systems

Whereas there is a number of methods and algorithms to learn regular languages, moving up the Chomsky hierarchy is proving to be a challenging task. Indeed, several theoretical barriers make the class of context-free languages hard to learn. To tackle these barriers, we choose to change the way we represent these languages. Among the formalisms that allow the definition of classes of languages, the one of string-rewriting systems (SRS) has outstanding properties. We introduce a new type of SRS’s, called Delimited SRS (DSRS), that are expressive enough to define, in a uniform way, a noteworthy and non trivial class of languages that contains all the regular languages, , , the parenthesis languages of Dyck, the language of Lukasiewicz, and many others. Moreover, DSRS’s constitute an efficient (often linear) parsing device for strings, and are thus promising candidates in forthcoming applications of grammatical inference. In this paper, we pioneer the problem of their learnability. We propose a novel and sound algorithm (called LARS) which identifies a large subclass of them in polynomial time (but not data). We illustrate the execution of our algorithm through several examples, discuss the position of the class in the Chomsky hierarchy and finally raise some open questions and research directions. This work was supported in part by the IST Program of the European Community, under the PASCAL Network of Excellence, IST-2002-506778. This publication only reflects the authors’ views. Editor: Georgios Paliouras and Yasubumi Sakakibara     

Stability of sitting postures: the influence of degrees of freedom

Observational studies of sitting have shown that, during spontaneous sitting, people adopt a variety of postures. Various researchers have formulated theories to explain why people adopt their sitting postures. Branton (1969) hypothesized that there is continual need for postural stability while sitting. Dempster (1955) stated that additional stability could be obtained through temporarily closing chains of body segments, or, in other words, through decreasing the number of degrees of freedom of the body. The present study elaborates on Dempster's theory. The aim of this study was to determine the influence of the degrees of freedom of the body on postural stability in sitting postures. For 21 different sitting postures, the total number of degrees of freedom was determined. Postural sway, a measure for postural stability, was determined using a 3D motion and position measurement system with ten healthy subjects. This study shows that the mean path length at the level of the second thoracic vertebra (PL0.05), a measure derived from postural sway, increases significantly (p < 0.0001) with an increase of the number of degrees of freedom of the body (DoFB). Closer examination of the data showed that a model taking into account only the degrees of freedom of the lumbar and thoracic spine and pelvis seems to be a better predictor of postural sway than the total number of degrees of freedom of the body.     

Algorithms for the Homogeneous Set Sandwich Problem

A homogeneous set is a non-trivial module of a graph, i.e. a non-empty, non-unitary, proper subset of a graph's vertices such that all its elements present exactly the same outer neighborhood. Given two graphs the Homogeneous Set Sandwich Problem (HSSP) asks whether there exists a sandwich graph which has a homogeneous set. In 2001 Tang et al. published an all-fast algorithm which was recently proven wrong, so that the HSSP's known upper bound would have been reset thereafter at the former determined by Cerioli et al. in 1998. We present, notwithstanding, new deterministic algorithms which have it established at We give as well two even faster randomized algorithms, whose simplicity might lend them didactic usefulness. We believe that, besides providing efficient easy-to-implement procedures to solve it, the study of these new approaches allows a fairly thorough understanding of the problem.     

How causal knowledge simplifies decision-making

Making decisions can be hard, but it can also be facilitated. Simple heuristics are fast and frugal but nevertheless fairly accurate decision rules that people can use to compensate for their limitations in computational capacity, time, and knowledge when they make decisions [Gigerenzer, G., Todd, P. M., & the ABC Research Group (1999). Simple Heuristics That Make Us Smart. New York: Oxford University Press.]. These heuristics are effective to the extent that they can exploit the structure of information in the environment in which they operate. Specifically, they require knowledge about the predictive value of probabilistic cues. However, it is often difficult to keep track of all the available cues in the environment and how they relate to any relevant criterion. This problem becomes even more critical if compound cues are considered. We submit that knowledge about the causal structure of the environment helps decision makers focus on a manageable subset of cues, thus effectively reducing the potential computational complexity inherent in even relatively simple decision-making tasks. We review experimental evidence that tested this hypothesis and report the results of a simulation study. We conclude that causal knowledge can act as a meta-cue for identifying highly valid cues, either individual or compound, and helps in the estimation of their validities.