Coloured Petri nets and graphical simulation for the validation of a robotic cell in aircraft industry

This paper proposes a mixed validation approach based on coloured Petri nets and 3D graphic simulation for the design of supervisory systems in manufacturing cells with multiple robots. The coloured Petri net is used to model the cell behaviour at a high level of abstraction. It models the activities of each cell component and its coordination by a supervisory system. The graphical simulation is used to analyse and validate the cell behaviour in a 3D environment, allowing the detection of collisions and the calculation of process times. The motivation for this work comes from the aeronautic industry. The automation of a fuselage assembly process requires the integration of robots with other cell components such as metrological or vision systems. In this cell, the robot trajectories are defined by the supervisory system and results from the coordination of the cell components. The paper presents the application of the approach for an aircraft assembly cell under integration in Brazil. This case study shows the feasibility of the approach and supports the discussion of its main advantages and limits. (C) 2011 Elsevier Ltd. All rights reserved.

The BCD transient recorder revisited: firmware for the ISA-to-USB bridging card and software for the graphical user interface

This report describes recent updates to the custom-built data-acquisition hardware operated by the Center for Hypersonics. In 2006, an ISA-to-USB bridging card was developed as part of Luke Hillyard's final-year thesis. This card allows the hardware to be connected to any recent personal computers via a (USB or RS232) serial port and it provides a number of simple text-based commands for control of the hardware. A graphical user interface program was also updated to help the experimenter manage the data acquisition functions. Sampled data is stored in text files that have been compressed with the gzip for mat. To simplify the later archiving or transport of the data, all files specific to a shot are stored in a single directory. This includes a text file for the run description, the signal configuration file and the individual sampled-data files, one for each signal that was recorded.

A Graphical Representation Model for Telemedicine and Telehealth Center Sustainability

This study shows the creation of a graphical representation after the application of a questionnaire to evaluate the indicative factors of a sustainable telemedicine and telehealth center in Sao Paulo, Brazil. We categorized the factors into seven domain areas: institutional, functional, economic-financial, renewal, academic-scientific, partnerships, and social welfare, which were plotted into a graphical representation. The developed graph was shown to be useful when used in the same institution over a long period and complemented with secondary information from publications, archives, and administrative documents to support the numerical indicators. Its use may contribute toward monitoring the factors that define telemedicine and telehealth center sustainability. When systematically applied, it may also be useful for identifying the specific characteristics of the telemedicine and telehealth center, to support its organizational development.

An approach for graphical user interface bad smells detection

In the context of an e ort to develop methodologies to support the evaluation of interactive system, this paper investigates an approach to detect graphical user interface bad smells. Our approach consists in detecting user interface bad smells through model-based reverse engineering from source code. Models are used to de ne which widgets are present in the interface, when can particular graphical user interface (GUI) events occur, under which conditions, which system actions are executed, and which GUI state is generated next.

Arrow Plot: a new graphical tool for selecting up and down regulated genes and genes differentially expressed on samples subgroups

Background: A common task in analyzing microarray data is to determine which genes are differentially expressed across two (or more) kind of tissue samples or samples submitted under experimental conditions. Several statistical methods have been proposed to accomplish this goal, generally based on measures of distance between classes. It is well known that biological samples are heterogeneous because of factors such as molecular subtypes or genetic background that are often unknown to the experimenter. For instance, in experiments which involve molecular classification of tumors it is important to identify significant subtypes of cancer. Bimodal or multimodal distributions often reflect the presence of subsamples mixtures. Consequently, there can be genes differentially expressed on sample subgroups which are missed if usual statistical approaches are used. In this paper we propose a new graphical tool which not only identifies genes with up and down regulations, but also genes with differential expression in different subclasses, that are usually missed if current statistical methods are used. This tool is based on two measures of distance between samples, namely the overlapping coefficient (OVL) between two densities and the area under the receiver operating characteristic (ROC) curve. The methodology proposed here was implemented in the open-source R software. Results: This method was applied to a publicly available dataset, as well as to a simulated dataset. We compared our results with the ones obtained using some of the standard methods for detecting differentially expressed genes, namely Welch t-statistic, fold change (FC), rank products (RP), average difference (AD), weighted average difference (WAD), moderated t-statistic (modT), intensity-based moderated t-statistic (ibmT), significance analysis of microarrays (samT) and area under the ROC curve (AUC). On both datasets all differentially expressed genes with bimodal or multimodal distributions were not selected by all standard selection procedures. We also compared our results with (i) area between ROC curve and rising area (ABCR) and (ii) the test for not proper ROC curves (TNRC). We found our methodology more comprehensive, because it detects both bimodal and multimodal distributions and different variances can be considered on both samples. Another advantage of our method is that we can analyze graphically the behavior of different kinds of differentially expressed genes. Conclusion: Our results indicate that the arrow plot represents a new flexible and useful tool for the analysis of gene expression profiles from microarrays.

Data mining with graphical models

Data Mining, Learning from data, graphical models, possibility theory

Graphical simulators for AUV development

A long development time is needed from the design to the implementation of an AUV. During the first steps, simulation plays an important role, since it allows for the development of preliminary versions of the control system to be integrated. Once the robot is ready, the control systems are implemented, tuned and tested. The use of a real-time simulator can help closing the gap between off-line simulation and real testing using the already implemented robot. When properly interfaced with the robot hardware, a real-time graphical simulation with a "hardware in the loop" configuration, can allow for the testing of the implemented control system running in the actual robot hardware. Hence, the development time is drastically reduced. These paper overviews the field of graphical simulators used for AUV development proposing a classification. It also presents NEPTUNE, a multi-vehicle, real-time, graphical simulator based on OpenGL that allows hardware in the loop simulations

Comparing and validating hypothesis test procedures: Graphical and numerical tools

When the behaviour of a specific hypothesis test statistic is studied by aMonte Carlo experiment, the usual way to describe its quality is by givingthe empirical level of the test. As an alternative to this procedure, we usethe empirical distribution of the obtained \emph{p-}values and exploit itsinformation both graphically and numerically.

Using graphical probability analysis (Bayes Nets) to evaluate a conditional DNA inclusion

This paper discusses the analysis of cases in which the inclusion or exclusion of a particular suspect, as a possible contributor to a DNA mixture, depends on the value of a variable (the number of contributors) that cannot be determined with certainty. It offers alternative ways to deal with such cases, including sensitivity analysis and object-oriented Bayesian networks, that separate uncertainty about the inclusion of the suspect from uncertainty about other variables. The paper presents a case study in which the value of DNA evidence varies radically depending on the number of contributors to a DNA mixture: if there are two contributors, the suspect is excluded; if there are three or more, the suspect is included; but the number of contributors cannot be determined with certainty. It shows how an object-oriented Bayesian network can accommodate and integrate varying perspectives on the unknown variable and how it can reduce the potential for bias by directing attention to relevant considerations and distinguishing different sources of uncertainty. It also discusses the challenge of presenting such evidence to lay audiences.

Graphical probabilistic analysis of the combination of items of evidence

Unlike the evaluation of single items of scientific evidence, the formal study and analysis of the jointevaluation of several distinct items of forensic evidence has to date received some punctual, ratherthan systematic, attention. Questions about the (i) relationships among a set of (usually unobservable)propositions and a set of (observable) items of scientific evidence, (ii) the joint probative valueof a collection of distinct items of evidence as well as (iii) the contribution of each individual itemwithin a given group of pieces of evidence still represent fundamental areas of research. To somedegree, this is remarkable since both, forensic science theory and practice, yet many daily inferencetasks, require the consideration of multiple items if not masses of evidence. A recurrent and particularcomplication that arises in such settings is that the application of probability theory, i.e. the referencemethod for reasoning under uncertainty, becomes increasingly demanding. The present paper takesthis as a starting point and discusses graphical probability models, i.e. Bayesian networks, as frameworkwithin which the joint evaluation of scientific evidence can be approached in some viable way.Based on a review of existing main contributions in this area, the article here aims at presentinginstances of real case studies from the author's institution in order to point out the usefulness andcapacities of Bayesian networks for the probabilistic assessment of the probative value of multipleand interrelated items of evidence. A main emphasis is placed on underlying general patterns of inference,their representation as well as their graphical probabilistic analysis. Attention is also drawnto inferential interactions, such as redundancy, synergy and directional change. These distinguish thejoint evaluation of evidence from assessments of isolated items of evidence. Together, these topicspresent aspects of interest to both, domain experts and recipients of expert information, because theyhave bearing on how multiple items of evidence are meaningfully and appropriately set into context.

A Graphical Pattern Editor for Java Frameworks

Ohjelmistojen uudelleenkäyttö on hyvin tärkeä käsite ohjelmistotekniikan alueella.Ohjelmistojen uudelleenkäyttötekniikat parantavat ohjelmistokehitysprosessin laatua. Yleisiä ratkaisuja sekä ohjelmiston suunnittelun että arkkitehtuurin uudelleenkäyttöön ovat olio-ohjelmointi ja sovelluskehykset. Tähän asti ei ole ollut olemassa yleisiä tapoja sovelluskehysten erikoistamiseen. Monet nykyääntunnetuista sovelluskehyksistä ovat hyvin suuria ja mutkikkaita. Tällaisten sovelluskehyksien käyttö on monimutkaista myös kokeneille ohjelmoijille. Hyvin dokumentoidut uudelleenkäytettävät sovelluskehyksen rajapinnat parantavat kehyksen käytettävyyttä ja tehostavat myös erikoistamisprosessiakin sovelluskehyksen käyttäjille. Sovelluskehyseditori (framework editor, JavaFrames) on prototyyppityökalu, jota voidaan käyttää yksinkertaistamaan sovelluskehyksen käyttöä. Perusajatus JavaFrames lähestymistavassa ovat erikoistamismallit, joita käytetään kuvamaan sovelluskehyksen uudelleenkäytettäviä rajapintoja. Näihin malleihin perustuen JavaFrames tarjoaa automaattisen lähdekoodi generaattorin, dokumentoinninja arkkitehtuurisääntöjen tarkistuksen. Tämä opinnäyte koskee graafisen mallieditorin kehittämistä JavaFrames ympäristöön. Työssä on laadittu työkalu,jonka avulla voidaan esittää graafisesti erikoistamismalli. Editori sallii uusien mallien luomisen, vanhojen käyttämättä olevien poistamisen, kuten myös yhteyksien lisäämisen mallien välille. Tällainen graafinen tuki JavaFrames ympäristöönvoi huomattavasti yksinkertaistaa sen käyttöä ja tehdä sovellusten kehittämisprosessista joustavamman.

Value chain analysis in graphical boards business

Tällä tutkielmalla oli kaksi tavoitetta. Ensimmäinen tavoite oli selvittää, kuinka valittujen tuotteiden arvoa asiakkaiden silmissä voisi lisätä. Toisena tavoitteena oli selvittää tuotteiden arvon lisääntyminen arvoketjun jokaisella portaalla kartonkitehtaaltaloppuasiakkaalle. Tutkimuksen kohteena oli kolme erilaista arvoketjua. Tutkimusoli luonteeltaan kvalitatiivinen ja tarvittavat tiedot kerättiin haastatteluilla. Tutkimuksen tuloksena voidaan mainita, että asiakkaat arvostavat laskua kustannuksissa enemmän kuin lisähyötyjä. Myös prosentuaalinen arvonlisäys valittuihintuotteisiin arvoketjun eri portaissa saatiin selville. Tästä työstä on tehty kaksi versiota; tämä versio, joka tulee julkiseksi neljän vuoden salassapitoajan jälkeen, ja toinen versio, joka sisältää arkaluontoisempaa kustannusinformaatiotaja on siitä syystä kokonaan salainen.