Recognizing splicing languages: Syntactic monoids and simultaneous pumping We use syntactic monoid methods, together with an enhanced pumping lemma, to investigate the structure of splicing languages. We obtain an algorithm for deciding whether a regular language is a reflexive splicing language, but the general question remains open. Tom Head [9] introduced the notion of splicing in formal language theory as a model for certain types of biochemical operations on DNA. In his formulation there is an initial language representing an initial set of double-stranded DNA (dsDNA) and a set of splicing rules that model the action of enzymes that cut and paste the dsDNA. The smallest language containing the initial language and closed under application of the splicing rules is called the splicing language. This setup has been codified and generalized, and is now known as an H system, see [11] . Throughout this paper we shall consider only finite H systems, with a finite set of rules and a finite initial language.. There have been several extensions of Head's original definitions. Throughout this paper we use the definitions due to Pȃun [11] . Specifically, a splicing rule is a 4-tuple u, u , v , v of strings, which we can use to splice two strings xuu y and x v vy at the indicated sites uu and v v to produce the string xuvy.. Head's original definitions implicitly incorporated reflexivity and symmetry (see Section 4) . These conditions are necessary for an accurate biological representation of DNA splicing systems: they both are consequences of the idea that the only requirement for recombination of strands of dsDNA is correct Watson-Crick complementarity. These extra conditions are lost in Pȃun's definition of splicing so we shall be explicit when we need reflexivity or symmetry. In more recent work Pȃun et al. [14] use the term 2-splicing to indicate symmetry assumptions, and many authors assume symmetry as part of the definition. See [1, 4] for further comparison of splicing definitions, including a discussion of another extension due to Pixton.. One of Head's original problems was to determine the class of languages that arise as splicing languages. Culik and Harju [6] quickly proved that splicing languages are regular; their result was reproved in [16] and generalized in [17] . On the other hand, Gatterdam [7] produced the simple example (aa) * of a regular language that is not a splicing. language. The precise characterization of splicing languages within regular languages remains unknown. There are related results by Bonizzoni et al. [2, 3] . The main impetus for this paper is [10] , in which Head exploited the connection between constants (see Section 7) and reflexive splicing languages. Our main result in this paper (see Section 6) is an algorithm for determining whether a given regular language L is the splicing language determined by a reflexive H system.. In Section 5 we adapt Head's main theorem to prove a characterization theorem for reflexive splicing languages. The point of the characterization is that we do not need to consider iterated splicing; nor do we need to explicitly provide an initial language. Our approach, rather, is to produce a finite set of reflexive splicing rules that can be used to generate a given language if in fact such a rule set exists. Indeed there is no obvious limit on the necessary size of such a rule set. We demonstrate that there is a limit with regard to rule set size in Section 6. We calculate this bound and by so doing we introduce the final ingredient in our algorithm for detecting reflexive splicing languages.. Our detection of reflexive splicing languages is algorithmic, and the key to our algorithm is determining an upper bound on the size of a splicing system that can generate L. While we do not give a "conceptual" characterization of such languages in this paper, we present numerous examples that shed light on the significance of our results, and pose questions that point to the challenge of developing such a characterization.. Bonizzoni et al. [4] have proved a characterization of reflexive splicing languages which is equivalent to our Theorem 5.2. Their result gives a more explicit form for the structure of reflexive splicing languages, which might well be useful in improving our detection algorithm.. In order to develop our algorithm we first introduce the notion of a "tuple language". A tuple language is a subset of (A * ) k to which we can apply formal language techniques via an identification of (A * ) k with the set of strings over the augmented language A ∪ {#} which contains exactly k − 1 copies of the separator #. The elementary facts of this approach are covered in Section 2.. Our use of tuple languages is very simple, and is mainly for ease of exposition. For an example of a much more thorough approach see, for example, Culik [5] .. We express the splicing operation in terms of tuple languages, and by so doing we are able to establish a fundamental fact in Section 4: the set of splicing rules which leave a given regular language invariant is itself regular. This is important because a splicing language is of course invariant under splicing with its rule set.. In addition to introducing tuple languages in this paper, we introduce novel applications of several tools to the problem of characterizing reflexive splicing languages. One of the main tools is the syntactic monoid. The other main tool is Pixton's generalization of the pumping lemma for regular languages which we call the "simultaneous pumping lemma" or SPL. The SPL allows us to pump the same string in several different regular languages simultaneously. A proof of this lemma using the notion of tuple languages is presented in Section 3. We believe that the SPL will stand on its own and that it is applicable to formal language theory in general.. In Section 7 we revisit Head's paper [10] . Head's main result is that if there is a finite set of constants F for the regular language L so that L\A * FA * is finite, then L is a reflexive splicing language. We say such languages are finitely based on constants, or FBC, and we give a short proof of Head's original result based on our characterization theorem from Section 5. We then present another application of our detection methods, namely an algorithm to determine if a given regular language L has such a set of constants. Thus we answer the question Head posed in [10] .. Finally, in Section 8 we present a number of examples to illustrate the differences between different types of splicing languages. These examples demonstrate that our results concerning reflexive splicing languages are specific within that class. In particular, we give examples demonstrating that not all splicing languages generated by finite H systems are reflexive, and that some are symmetric while others are not.. Many of the results presented in this paper were addressed in the first author's Ph.D. dissertation [8] , although in most cases those that were proved there are given different proofs here. In particular, all results are now unified within the context of the tuple language approach using the syntactic monoid and the SPL. Further, within this unified context we have clarified the nature of the open questions still at hand.. Some of the results in this paper were announced at the DNA8 Workshop in Sapporo, see [12] .

O B I O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O B I O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Advances in Cheminformatics Methodologies and Infrastructure to Support the Data Mining of Large, Heterogeneous Chemical Datasets In recent years, there has been an explosion in the availability of publicly accessible chemical information, including chemical structures of small molecules, structure-derived properties and associated biological activities in a variety of assays. These data sources present us with a significant opportunity to develop and apply computational tools to extract and understand the underlying structure-activity relationships. Furthermore, by integrating chemical data sources with biological information (protein structure, gene expression and so on), we can attempt to build up a holistic view of the effects of small molecules in biological systems. Equally important is the ability for non-experts to access and utilize state of the art cheminformatics method and models. In this review we present recent developments in cheminformatics methodologies and infrastructure that provide a robust, distributed approach to mining large and complex chemical datasets. In the area of methodology development, we highlight recent work on characterizing structure-activity landscapes, QSAR model domain applicability and the use of chemical similarity in text mining. In the area of infrastructure, we discuss a distributed web services framework that allows easy deployment and uniform access to computational (statistics, cheminformatics and computational chemistry) methods, data and models. We also discuss the development of PubChem derived databases and highlight techniques that allow us to scale the infrastructure to extremely large compound collections, by use of distributed processing on Grids. Given that the above work is applicable to arbitrary types of cheminformatics problems, we also present some case studies related to virtual screening for anti-malarials and predictions of anti-cancer activity. The field of cheminformatics is multi-disciplinary and is an amalgam of chemistry, mathematics and computer science. Cheminformatics focuses on the development of methods and tools to address problems in the management and analysis of chemical information. Such information can be of a variety of types including chemical structure (in various formats such as SMILES, SDF, CML and so on) and derived aspects of chemical structure (such as number of atoms and various descriptors of structure). With the advent of large public repositories of chemical and biological data, there has been an explosion in the type and amount of data that is now available for cheminformatics analysis. Thus, we can now access chemical structures of millions of compounds, as well as the biological activities of many of these structures in a variety of biological assays. Public literature databases now allow one to move from chemical structure to specific documents and in some cases vice versa.. It is clear that there is a need to be able to connect chemical structure with biological information (which may include structures of biologically relevant macromolecules and biological activities). Given the rise of chemical biology and chemogenomics [Bredel2004], we must also look beyond information organization and handling issues and develop efficient tools and interfaces that will allow us to analyze chemical and biological information in an integrated fashion and obtain robust predictions of the biological effects of small molecules. This aspect is very important since it is now easy to collect information from a variety of high throughput experiments and vendor catalogues. As a result, though access to the data in a variety of modes (such as SQL queries, web service based queries and so on) is possible, it is important to consider that analysis tools and pipelines should also be able to access the data in a uniform and standardized manner and in the longer term, without human intervention.. These requirements are not unique to cheminformatics. Indeed computer scientists and software engineers have developed a wide array of systems that support the interlinking of geographically distributed computational resources. The idea of the modern Grid computing was first described by. [Foster1999] . This architecture aims to connect geographically distributed individual computers, clusters of computers, and more specialized parallel computing and mass storage resources, providing services and client libraries for remote job execution, distributed file management, resource information management, and integrated security. This architecture has merged with the more general Web service architecture. Generally all such systems are examples of Service Oriented Architecture, in which network accessible services with welldefined access (or programming) interfaces communicate with client applications using XMLencoded messages transmitted over HTTP. Typically the service interfaces are defined with the Web Service Description Language (WSDL) and messages are wrapped in SOAP. Alternative versions of this architecticture have also become popular. The Representation State Transfer (REST) style of Web services replaces WSDL with the basic HTTP operations GET, POST, PUT, and DELETE, which operate on URLs. The actual content of the URLs may be SOAP messages but also RSS and Atom XML formats are popular. Non-XML formats like JavaScript Object Notation (JSON) can also be used for messages. In any case, the general architecture approaches are similar, and the distinctions do not concern us here. The advantages to such an architecture are obvious: one is no longer restricted to a local machine and submitted jobs can be moved to the most appropriate machine (in terms of hardware configuration or availability). The NSF-funded t TeraGrid and the NSF and DOE-funded Open Science Grid are the two most prominent examples of Web service-based Grids for scientific computing within the United States.. There are a number of important aspects of such distributed infrastructures. First, the broad goal is to enable collaboration between different groups in an easy and efficient manner. Such collaborations will involve communication between people as well as machines, and will exchange a wide variety of data types (documents, chemical structures, assay readouts and so on). Second, to achieve efficiency, standards for interoperability are critical. Such standards apply to various parts of such an infrastructure including communication standards, data storage and annotation standards as well as authentication standards. Third, given the compute intensive nature of many chemical problems, easy access to powerful machines such as supercomputers and computational grids becomes important. Such infrastructures need to adhere to standards developed in the Web and Grid computing communities if they are to make use of such resources. In the area of cheminformatics, Guha et al [REF] have described the "Blue Obelisk", an umbrella organization of various open source projects, whose aim is to define and promulgate community-approved standard for various aspects of cheminformatics. There are many different features of distributed infrastructures and while a number of efforts in the chemical sciences community will be discussed in this paper, it should be noted that, all the projects do not aim to address all the features noted here. Indeed, this is the utility of such infrastructures -as long as they follow standards, they should be able to interoperate. We also note that a variety of other fields have developed distributed infrastructures and example include geography, biology and high energy physics and we do not discuss them in this paper and rather, focus on the chemical sciences.. It should be noted that a distributed infrastructure is not simply about linking computational resources. Indeed, the most common feature of such an infrastructure is the ability to connect data sources in a seamless fashion. This is especially important given the fact that we are faced with a deluge of data from a variety of sources. Clearly, no one person or organization is in a position to effectively analyze it all. As a result, such data sources must be made easily accessible. But it is not sufficient to allow easy connections to the sources. Flexible approaches must be provided to allow queries and combine results from different data sources. Though it is certainly true that simply having large amounts of data does not lead to insight, it is also true that no insight will be derived from such data collections if they cannot be analyzed in a flexible and efficient manner. This observation leads on to the fact that once data is accessible, analytic methods must be applied. The cheminformatics literature is replete with methods for various. tasks. Yet, analysis of real world data demands that robust and efficient implementations be available. Given the heterogeneity of today's computing infrastructure, it is natural to expect that analysis tools and methods will be accessible in a variety of ways. Traditionally, command line tools have been used by scientists, giving way to GUI's. However, both are generally restricted to local functionality, though many of today's tools can make use of resources on the Internet. As will be described later on, making such tools available as distributed services leads to a much more flexible analysis infrastructure -one that can be accessed from anywhere and that can be incorporated into any thing, be it a command line, GUI or workflow tool. Adopting this open service architecture is vital if we want academic chemical informatics research to prosper, as it enable new tools and pipelines to be developed from existing parts. Figure 1 pictorially demonstrates the evolution of distributed infrastructures from both a hardware and software perspective. In this paper we have presented a review of the start of the art in distributed systems designed to handle chemical information. With the rise in automated, high throughput systems, the large amounts of data that are being generated impose a number of requirements on a storage and analysis framework. First, the resultant data must be easily accessible using standardized protocols. While this is not always the case, the use of relational databases and standard web service protocols (such as SOAP) go a long way to allowing uniform and well defined access methods. Second, it is vital that we have methods that can analyze such data, to generate insight into the workings of the underlying chemical or biological systems. We have presented recent work carried out at the Indiana University Chemical Informatics Cyberinfrastructure and Collaboratory (CICC) that has focused on developing cheminformatics methodologies for a variety of tasks including QSAR, clustering, outlier detection and model domain applicability. In addition to methodology development, we have designed a web service based deployment infrastructure that is suitable for the large chemical datasets characteristic of modern drug discovery efforts. Many of these services provide convenient interfaces to both data sources and computational methods. In the latter case, we have provided SOAP-based web service methods to both cheminformatics and statistical methods. Along with developing methodoligies and infrastructure development, we have created data source derived from PubChem. Notable amongs them, is the Pub3D resource that provides single conformer 3D structures, for 99% of PubChem. The database allows retrieval of structures based on compound ID's or by 3D shape similarity searches and can be accessed by direct SQL or via SOAP web services. We have also described several case studies that have enabled collaboration between cheminformatics experts and non-experts, allowing the latter to make use of cheminformatics technologies without requiring expertise in cheminformatics or distributed systems.. The development of distributed infrastructures stresses the collaborative nature of scientific discovery. In the field of drug design, such an approach is vital given that multiple domains of expertise (chemistry, biology, computation) are required to fully understand chemical and biological systems. A distributed infrastructure, such as described here, allows multiple groups, with different domains of expertise to easily access and analyze a wide variety of chemical and biological data. Though cheminformatics has been in existence since the 1960's, it is only recently that large collections of chemical information have highlighted the need for infrastructures capable of handling them. At the same time, the ability to connect computers in networks as well connect networks themselves provides us with vast computing power, that in many cases is also cheap. The use of compute clusters, which are usually a collection of machines located in a single geographical location, is common in many areas of high-performance computing such as computational chemistry and biology. More recently, the ability to seamlessly utilize geographically dispersed computers and networks has led to a number of large, distributed, projects such as Folding@Home [Pande2003] . In both these cases, the focus is on enhancing computational power, by virtue of parallelization. The combination of distributed computer systems, large collections of chemical and biological information, and novel computational methodologies presents us with a new way to enhance the usage and accessibility of chemical information. By virtue of well-known standards to represent data and communicate between programs, we now have the ability to "mix and match" methods and data in an unprecedented fashion.. Various subfields of chemistry have developed and employed distributed infrastructures for a variety of purposes. A number of these efforts focus on compute-intensive tasks such as abinitio calculations whereas others represent infrastructures to store and disseminate chemical data (such as crystal structures). It is only recently that such infrastructures have been developed and deployed for problems in cheminformatics in general. In this section, we briefly survey past work that have employed distributed infrastructures in the chemical sciences. At this point, we should note that traditional definitions of cheminformatics can cover all the work described in this section. Thus, a cyberinfrastructure for ab-initio calculations could be described as a cheminformatics project. We choose to be a little narrower and consider individual infrastructures in terms of their application area. In this sense, a cheminformatics cyberinfrastructure would relate to tasks in the domain of cheminformatics such as predictive modeling, diversity analysis, virtual library generation and so on. Such an infrastructure would be distinct from say one designed to support crystallographic information, though of course, the two could interoperate with each other.. We first consider a distributed infrastructure designed to store and share crystallographic information. Cole et al [REF, REF] described an infrastructure, termed the ECSES environment, to share high-throughput crystallographic information that connected users, spread across the Internet, to instrumentation. The infrastructure allowed users to remotely monitor crystallographic experiments and perform the relevant analysis. For example, a user could provide a sample to the crystallography service and then view images from a diffractometer and evaluate unit cell parameters in real time, communicate with the instrument operator and so on. On completion, the crystallographic data is stored in a local database. The environment then allows a user to search databases remotely for crystal structures that are similar to the one generated. The ECSES environment was constructed using Grid (specifically, Globus Another distributed infrastructure for crystallography was described by Hunter et al [REF] . They developed AnnoCryst, a system that allowed users to collaboratively annotate crystal structures and share such annotations in a secure and asynchronous fashion. The system is designed such that annotations for a given crystal structure are stored in a secure fashion and can easily be linked to actual crystal records, which may be stored in arbitrary databases. An important focus of the system is the ability to allow groups of scientists to collaborate on annotations. Given that annotations are stored, security played an important role, to allow authentication of such annotations. The infrastructure was developed using a variety of open source components and made extensive use of published standards. For example, they employed Shibboleth [REF] to enable identity management and XACML to define and enforce access control policies. They also made extensive use of social networking standards such as FOAF to describe relationships between contributors and semantic web tools (such as Annotea for the storage of annotations) and standards such as RDF. The latter aspect is important since it allowed them to link to other semantic resources such as Connotea and the Protein Ontology as well as allow sophisticated semantic searches (using SPARQL) over the annotation collection. This project highlights that distributed infrastructures need not be restricted to computational services or data storage. Indeed, the AnnoCryst project combines data storage with collaborative interaction, allowing multiple distributed users to enhance entries in a wide range of crystal structure repositories.. Paolini and Bhattacharjee [REF] described the development of a web service infrastructure to access thermochemical data and calculations. They aggregated a variety of thermochemical data sources, such as NIST, NASA and CHEMKIN [REF] , into a relational database. In addition to storing reported data, they also performed a number of calculations to evaluate properties such as entropy and hat capacities. Access to the database is provided via SOAP based web services. They also highlighted the flexibility of these web services by incorporating them into Matlab and Microsoft Excel to generate formatted thermochemical data tables.. The field of computational chemistry has seen a number of grid computing initiatives. An early example is that of the Computational Chemistry Grid (CCG) [REF] . This project was a threetiered system consisting of a client side GUI, a middleware service and a resource layer. The middleware layer was based on Globus [REF] and its role was to distribute jobs across the Grid, based on a variety of parameters such as allocations and availability. The primary use of this grid was to run computational chemistry calculations such as Gaussian and NWChem. In a similar fashion, Truong et al [REF] developed a cyberinfrastructure for scientific computing termed CSE-Online. This project consisted of a centralized web portal that was the point of entry for users. Via this portal, a user would be able to access individual programs, upload datasets and extract results form prior runs. The actual computational services were provided by multiple, possible remote, servers hosting individual applications. The infrastructure also provided resource management tools such as job scheduling via PBS and job submission to the TeraGrid [REF] Communication between the portal and individual compute servers is performed via web services. In addition to the online portal, the project also developed a desktop interface to the portal which provided a variety of capabilities such as relational database for storage, visualization of results, generation of input scripts and so on. In terms of functionality, the infrastructure was oriented towards ab-initio calculations and molecular simulation. Sanna et al [REF] described the development of a Grid infrastructure for quantum chemistry computations using Gaussian [REF] . Their infrastructure was based on a three-tier architecture comprised of an interface tier (responsible for communications between the grid infrastructure and user clients), the grid tier (responsible for management of grid resources and scheduling) and finally the resource tier (responsible for the actual computations) and has been described by De Meo [REF] . It is interesting to note that the quantum computing grid described by Sanna was adapted from a Grid infrastructure developed for a bioinformatics applicationhighlighting the generality of this approach.. Finally, we consider efforts to develop distributed infrastructure specifically in the area of cheminformatics. An early effort at a distributed infrastructure for chemical information is the World Wide Molecular Matrix (WWMM) developed by Murray-Rust and co-workers at Cambridge University. The focus of this project was the development of web services that would provide access to data sources (usually some form of relational database) and methods (such as format conversions). As part of this project, they also investigated the use of XML databases (specifically XIndice) for efficient storage and querying of CML [Murray-Rust1999] documents.. In 2005, the NIH funded several groups (including Indiana University) under the Molecular Libraries Initiative (MLI) [Austin2004] . These groups were termed Exploratory Centers for Cheminformatics Research (ECCR) and were tasked with extending the state of the art in cheminformatics research. Though much of the research focused on methodology development, a significant aspect of their work was in providing access to tools, methods and data. For example, the University of North Carolina have developed CarolineChemBench (http://ceccr.unc.edu/) which is a web interface to a wide variety of tools, primarily focusing on QSAR modeling. As the name suggests, the application aims to be a web-based workbench for QSAR modeling. It provides access to a number of molecular descriptors and machine learning methods. A similar application was developed at the Renssalear Polytechnic Institute, which focused on a descriptor development and machine learning methods for QSAR modeling (http://reccr.chem.rpi.edu/). As with the UNC efforts, their tools were exposed in the form of a web application that allowed users to upload data and develop predictive models. Characteristic of both these efforts is that access to their tools and methods is strictly via a web application. In other words, a user must navigate to their web page and use the functionality provided by the developers. For many cases, this is sufficient. However, it is can be an inflexible approach at times and does not allow one to "mix and match" methods. North Caroline State University was also designated an ECCR and their focus was on machine learning methods and validation methods for statistical models. They developed a web application in which users could upload data and automatically develop a series of predictive models. As part of their work, they developed a tool called PowerMV [REF] which is a standalone tool to examine SD files and generate a wide variety of molecular descriptors. This tool was employed by their web application, in the backend, to provide input to the machine learning algorithms.. Apart from the NIH funded groups mentioned above, a number of other workers have developed infrastructure for various cheminformatics tasks. For example, Sild et al [Sild2006] have described a Grid infrastructure termed OpenMolGRID which connects geographically distributed computational resources to provide seamless access to data and applications. Their infrastructure was comprised of three main components: a data warehouse, data mining module and molecular engineering module. These high level modules are based on the UNICORE [Romberg2002] Grid middleware. More specifically, they incorporated tools such as CODESSA Pro and MOPAC, which were linked into workflows using MetaPlugin [Sild2005] allowing users to automate the QSAR modeling process across the Grid.. Karthikeyan et al [REF] described a distributed infrastructure, termed ChemSTAR based on Java Remote Method Invocation (RMI) to distribute molecular descriptor calculations over multiple machines. They employed this infrastructure to rapidly evaluate molecular descriptors for 11 million molecules. This infrastructure differs from OpenMolGRID in that it does not use a standard middleware such as Globus or UNICORE. In this sense, the use and deployment of ChemSTAR is not as seamless as some other infrastructures. It should also be noted that other projects such as VCCLAB [REF] have also employed a Java RMI approach to connect geographically distributed resources to provide access to various cheminformatics and data mining tools via a single point of entry. As with OpenMolGrid, it employs a three-tier architecture in which users employ a local client (written as a Java applet), which communicates with a "SuperServer" acting as the middleware between the client applet and the actual compute servers. A number of workers have co-opted these technologies to develop novel applications in cheminformatics. This is not surprising since chemical information is extremely diverse (ranging from structural information, patents and journal articles to drug targets, side effects and pathway information) and traditional methods of storage and manipulation do not always make the links between individual concepts apparent.. Much of the work in this area, as applied to chemistry builds on the seminal work by MurrayRust and co-workers in developing an XML format to represent chemical data, termed Chemical Markup Language (CML) [REF] . An early application of CML to represent the semantics of chemical information was CMLRSS [REF] , which was used to enhance RSS feeds with chemical data. Casher et al [REF] described an ontology, termed SemanticEye, to enhance the extractability of chemical information from various documents (primarily PDF) and store such information in an RDF repository. Some examples of the information they extracted included document metadata (encoded as Adobe XMP within a PDF), Digital Object Identifiers (DOI) and structures represented as InChI's. They also developed a browser-based interface allowing users to explore the metadata repository and examine individual documents or even aggregate documents based on their semantic relationships (such as similarity based on the InChI's contained within the documents). Taylor et al [REF] also described the use of RDF to represent and store chemical information. An important aspect of their presentation was the ability to incorporate provenance information into the repositories. They also examined the use of triplestores to store chemical information and their behavior with respect to size of the collection. They performed benchmarks such as chained RDF queries and insertion of RDF files into the triple-store and showed that they could obtain reasonable performance with up to 36 million triples (representing the unique molecules from the. Another project in the area of semantic chemistry being carried out by the Royal Society of Chemistry and is termed Project Prospect. The goal of this project was to markup journal articles in the field of chemistry such that one could link articles to other source of information in a semantic manner (as opposed to direct URL's). Thus, they employed the Gene Ontology [REF] and Gold Book [REF] to identify terms within the documents, highlighting them on the fly. In addition, they were able to extract chemical entities using OSCAR3 [Corbett2006] and display chemical structures for the entities that were successfully extracted. Though restricted to chemistry journal articles, this project highlights the utility of semantic markup, since searches over a document collection can employ not only exact or fuzzy textual matches, but also perform semantic queries that make use of the extracted metadata.

O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B O O O O O B O B O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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On the Way to Large-Scale and High-Resolution Brain-Chip Interfacing Abstract Brain-chip-interfaces (BCHIs) are hybrid entities where chips and nerve cells establish a close physical interaction allowing the transfer of information in one or both directions. Typical examples are represented by multisite-recording chips interfaced to cultured neurons, cultured/acute brain slices, or implanted ''in vivo''. This paper provides an overview on recent achievements in our laboratory in the field of BCHIs leading to enhancement of signals transmission from nerve cells to chip or from chip to nerve cells with an emphasis on in vivo interfacing, either in terms of signal-to-noise ratio or of spatiotemporal resolution. Oxide-insulated chips featuring large-scale and high-resolution arrays of stimulation and recording elements are presented as a promising technology for high spatiotemporal resolution interfacing, as recently demonstrated by recordings obtained from hippocampal slices and brain cortex in implanted animals. Finally, we report on an automated tool for processing and analysis of acquired signals by BCHIs.Keywords Brain-chip interfacing Á Electrolyte-oxidesemiconductor field effect transistors Á Electrolyte-oxidesemiconductor capacitors Á Multi transistor arrays Á Multi electrode arrays Á Local field potentials Á Neuronal signal analysis

O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O B I I O B I I O B I I O B I I


Applying RBF Neural Nets for Position Control of an Inter/Scara Robot Abstract: This paper describes experimental results applying artificial neural networks to perform the position control of a real scara manipulator robot. The general control strategy consists of a neural controller that operates in parallel with a conventional controller based on the feedback error learning architecture. The main advantage of this architecture is that it does not require any modification of the previous conventional controller algorithm. MLP and RBF neural networks trained on-line have been used, without requiring any previous knowledge about the system to be controlled. These approach has performed very successfully, with better results obtained with the RBF networks when compared to PID and sliding mode positional controllers. This paper describes and discusses practical results obtained with the use of computational intelligence techniques, specifically artificial neural networks, applied to the position control of a real manipulator robot. The neural controller proposed in this work was applied in a real scara robot installed at the Industrial Automation Laboratory of the Federal University of Santa Catarina, Brazil. The work is the result of a cooperation between the Automation and Mechanical Engineering departments. The robot was manufactured by the Institute of Robotics (IfR) of the ETH (Swiss Federal Institute of Technology, http://www.ifr.mavt.ethz.ch/ ). Differently from most industrial manipulator robots, this one has an open architecture, which allows the implementation of any type of control law. The main purpose was to evaluate new algorithms for position/force control, since the robot is also equipped with a force sensor. Fig. 1 shows the Inter/Scara robot.. Manipulator robots are a type of non-linear and time variant systems. Conventional controllers, such as PD and PID, are used among other advanced and robust controllers that require some knowledge about the dynamic model of the system under control. In the case of manipulator robots, it is difficult to obtain some parameters, as the inertia matrix and mass centers of any joint, with sufficient accuracy. Therefore, either adaptive controller are required to overcome these inaccurate parameters or control laws based on Lyapunov functions are developed to guarantee some kind of stability [1] . Both approaches require some knowledge about the system. This work explores a computational intelligence technique, namely artificial neural networks, to deal with this situation. In particular, control algorithms based on neural networks and fuzzy logic techniques are considered intelligent control approaches that do not require any previous knowledge about the system to be controlled. The main goal of this work is to explore an effective computational intelligence technique to control this complex system using a structure as simple as possible, with preference to one that requires less change in the previous conventional controller that has installed in the system, do not overload the main processor and is robustness against disturbance and load effect variations. This paper has presented a practical and successful application of a neural controller performing in parallel with a conventional controller in the position and trajectory following control of a real robot. The use of a conventional controller performing in parallel with the NNs is advantageous to maintain the robustness of the system when the NN become saturated (due to high learning rates) and it is important to force the readjustment of the synaptic weights of the NN used when the robot changes its configuration. As soon as the NN captures the dynamic behavior of the system, the final torque is given quite totally by the NN and a higher performance could be achieved. Both the MLP and RBF ANN perform very well, Note: values expressed in microseconds (µs).. Even if computer resources are short, a simple PD+MLP with one hidden layer allows better results than a PD controller. Otherwise, if higher processing power is available, a PID+RBF achieves the best results. Since the neural controllers proposed here have performed very successfully, future directions of this works intend to establish an integrated position/force control over a hybrid control architecture to deal with robot applications that imply some contact with the environment.

O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Socio-Cultural Imbalances in AIED Research: Investigations, Implications and Opportunities Abstract This paper investigates international representations in the Artificial Intelligence in Education (AIED) research field. Its methodological and theoretical groundings are inspired by Arnett (2008) and Henrich et al. (2010a) who addressed the same issue in psychology, and respectively a) discovered massive imbalances in representation in top-tier psychology journals, and b) clarified risks of this situation. Data on research production collected on 2 top-tiers AIED conferences indicate that relatively similar imbalances exist in AIED. Potential threats and challenges induced by that situation are discussed as well as additionally identified phenomena related to the culture of the AIED community. The Artificial Intelligence in Education (AIED) research field aims to develop technologies for improving existing educational knowledge and practices, creating new ones, and/or overcoming a lack of teaching opportunities and specialists. Findings from multiple research disciplines are merged to achieve these objectives, with computer science and psychology being the historical cornerstones of this interdisciplinary research field.. As with any other scientific domain, AIED has to rely on theoretical foundations, which are most often provided by psychology and related domains in the humanities. Indeed, since its emergence as an individual research field, psychology has suggested educational problems to be addressed by AIED researchers. It has guided these scholars in defining novel education-related use of computer science techniques, or in proposing original approaches. Consequently, psychology currently has a key influence on many features of AIED systems such as their design, internal mechanisms, graphical user interfaces, and expected human-computer interactions.. In 2008, Jeffrey Arnett published an influential survey paper in American Psychologist (Arnett 2008) whose objective was to investigate international representations in contemporary psychology research production. Data that Arnett collected demonstrated that US and, more generally, Western, Educated, Industrialized, Rich, and Democratic (WEIRD) 1 societies have an extreme dominance on psychology content production, both in terms of authorship and sample representations. Arnett concluded his paper by stating that the reported dominance is so high it could negatively affect psychology as a human science.. Influenced by the work of Arnett and other similar studies, Joseph Henrich and colleagues later released an extensive interdisciplinary review to determine whether typical psychology samples are related to populations that are similar enough to the rest of humankind for generalization (Henrich et al. 2010a, b) . Although the survey identifies evidence of universalisms, it also reports numerous studies that describe cognitive and behavioral socio-cultural variations between the limited populations used in psychology samples and other human groups.. Inspired by the studies of Arnett and Henrich et al. , the objectives of this paper are threefold:. -to discuss potential implications for AIED of socio-cultural imbalances detected in psychology, -to assess whether international representations in AIED are similarly imbalanced, and if so, -to discuss potential implications of AIED imbalances and strategies to address them.. The next section describes prior investigations of international representations in psychology and more specifically the work of Arnett (2008) and Henrich et al. (2010a) . Then, a similar investigation of international representations in AIED is described, followed by commentaries collected from an international panel of AIED researchers and additional notes from the author of this paper. During the writing of this paper, extreme care was put into providing an accurate presentation of data on international representations in AIED authorship and sampling. The section summarizing the commentaries of a panel of AIED experts was written with a dedicated attentiveness towards achieving a balanced and honest description of all the contributions.. Culture is a sensitive topic, and researchers all convey a personal ecology of interpretations. Despite considerable effort to limit this effect, which includes the collection of commentaries by researchers with different cultural backgrounds, it is acknowledged that personal positions of the author may have inadvertently influenced the design and writing of this paper, just as it may influence the interpretations drawn by some readers. Therefore, final clarifications are provided in this section to limit misunderstandings.. It cannot be ignored that the data described in this paper could be used to nurture a dangerous struggle for influence between schools of thoughts that could only be detrimental to AIED research. However, the author strongly believes that the community holds all the wisdom it needs to ensure that the suggested debate remains productive and focused on the improvement of the field. Data provided in this paper could indeed be used to ground fair and informed discussions:. -first and foremost on the limited cultural diversity of the AIED research field and whether actions have to be undertaken for its greater good, -but also on the current culture of its interdisciplinary community and whether its evolution is appropriate for efficiently tackling all the possible research questions related to it.. Overall the position advocated in this paper is threefold:. -detected imbalances are dangerously strong and may pose a threat to the quality of the AIED research.. -'quality' must remain the main determinant of research acceptance and diffusion, but its definition changes between disciplines, and it may also have culturallyvariable interpretations as well, -a consensual situation for AIED to better consider diversity in its various facets can be reached with more involvement of the community.. It must also be clarified that it has never been the objective of this paper (nor the one of Arnett 2008 or Henrich et al. 2010a to suggest that research production should be constrained, such as for example by country quotas. One should indeed keep in mind that observed imbalances in AIED are the result of unconscious processes, economical differences, and historical aspects among other factors. This partly explains that imbalances in research production are in the natural order of things. However, they should be better controlled and moderated.. It is finally important to insist that the WEIRD vs non-WEIRD dichotomy, the main granularity level used in this paper (and in Arnett 2008 and Henrich et al. 2010a ) for discussing cultural differences, has mainly been selected for reasons of convenience. It is a satisfying-enough approach for supporting the message of this paper, that culture should be better taken into account in AIED. However there are no claims that it is the best perspective to embed cultural awareness in AIED systems, nor that discussing cultural differences from a country or country-cluster standpoints are the sole valid approaches since cultural groups vary in criteria that define them (see Blanchard 2012b) .. Overall this paper probably brings many more questions than answers, and this is a deliberate approach. There is currently a lack of studies and results on the real impact and influences of cultures on the AIED field. Providing assumptions and claims at this stage would thus be likely to end up in the expression of cultural stereotypes, which would be detrimental to this emerging research trend that is obviously in an exploratory phase.. Indeed, appropriately addressing cultural diversity is possibly one of the most complicated AIED topics to consider (see Blanchard and Mizoguchi 2014; Blanchard and Ogan 2010) . It will require time and systematic analyses. It also requires that researchers avoid jumping to conclusions too easily. But the possibility to have a universal impact on human beings is real, and should be appealing to members of the community.. Finally, and to paraphrase a former US president, the AIED community should choose to embrace this challenge not because it is easy, but because it is hard, and because it could serve to organize and measure the best of the energies and skills of this community. The methodology employed here was largely inspired by the one described in Arnett (2008) , and consisted of analyzing AIED research. Consequently, full paper publications in two AIED-related international conferences were analyzed over a period of 12 years (2002) (2003) (2004) (2005) (2006) (2007) (2008) (2009) (2010) (2011) (2012) (2013) . Selected conferences were the International Conference on Intelligent Tutoring Systems (ITS) and the International Conference on Artificial Intelligence in Education.. A conference-focused analysis was preferred to the journal-based approach of Arnett because the AIED community includes scholars from several different disciplines. Therefore journal publications dedicated to AIED research are spread not only among the few journals dedicated to the field but also among many others that are discipline-specific.. AIED and ITS conferences were chosen because their content is expected to correctly reflect state-of-the-art AIED research production.. 6 They are commonly acknowledged as the two top-tier conferences for AIED research, and are perceived as major yearly events for the AIED community. Although other conferences of quality exist (e.g., ICCE, ECTEL, ICALT), it is commonly agreed that no other event has achieved a similar level of international recognition in the AIED field. Both selected conferences are biennial: ITS2002 occurred in France and Spain, AIED2003 in the USA, ITS2004 in Brazil, AIED2005 in the Netherlands, ITS2006 in Taiwan, AIED2007 in the USA, ITS2008 in Canada, AIED2009 in UK, ITS2010 in the USA, AIED2011 in New Zealand, ITS2012 8 in Greece, and AIED2013 in the USA. Origins were coded according to the following categories: USA and English countries (Canada, Australia, New Zealand, UK, and Ireland) were considered separately as in Arnett (2008) whereas other categories were related to continents: Europe, Asia, 9 and Africa.. 10 A Latin America category was also considered and was essentially composed of entries from South America and Mexico.

O O O O O O O O O O O O O O O O O B I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O B I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Swarm intelligence algorithms for macroscopic traffic flow model validation with automatic assignment of fundamental diagrams The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. This paper is concerned with the problem of macroscopic road traffic flow model calibration and verification. Thoroughly validated models are necessary for both control system design and scenario evaluation purposes. Here, the second order traffic flow model METANET was calibrated and verified using real data.A powerful optimisation problem formulation is proposed for identifying a set of model parameters that makes the model fit to measurements. For the macroscopic traffic flow model validation problem, this set of parameters characterise the aggregate traffic flow features over a road network. In traffic engineering, one of the most important relationships whose parameters need to be determined is the fundamental diagram of traffic, which models the non-linear relationship between vehicular flow and density. Typically, a real network does not exhibit the same traffic flow aggregate behaviour everywhere and different fundamental diagrams are used for covering different network areas. As a result, one of the initial steps of the validation process rests on expert engineering opinion assigning the spatial extension of fundamental diagrams. The proposed optimisation problem formulation allows for automatically determining the number of different fundamental diagrams to be used and their corresponding spatial extension over the road network, simplifying this initial step. Although the optimisation problem suffers from local minima, good solutions which generalise well were obtained.The design of the system used is highly generic and allows for a number of evolutionary and swarm intelligence algorithms to be used. Two UK sites have been used for testing it. Calibration and verification results are Preprint submitted to Applied Soft Computing September 18, 2015 discussed in detail. The resulting models are able to capture the dynamics of traffic flow and replicate shockwave propagation. A total of ten different algorithms were considered and compared with respect to their ability to converge to a solution, which remains valid for different sets of data. Particle Swarm Optimisation (PSO) algorithms have proven to be particularly effective and provide the best results both in terms of speed of convergence and solution generalisation. An interesting result reported is that more recently proposed PSO algorithms were outperformed by older variants, both in terms of speed of convergence and model error minimisation. This paper has presented a study on the application of population based optimisation methods to the problem of macroscopic traffic flow model cali- bration and verification. The suggested problem formulation treats the traffic simulator as a black box and therefore the METANET program used can easily be replaced by another executable. The network's spatial and temporal discretisation is model dependent and does not depend on the location of the sensors. A simple geographic mapping is sufficient for the followed approach to deliver excellent solutions given an appropriate algorithm.. Furthermore, the results demonstrate the feasibility of achieving AAFD through the suggested problem formulation. This way, expert engineering opinion is removed from the calibration effort. It has been shown that the derived solutions are able to detect the capacity pattern of a particular network, although some cautious analysis needs to take place. These benefits have become possible to be realised thanks to the nature of the optimisation algorithms used.. Ten different algorithms have been implemented and evaluated in this paper. A simple GA acting as baseline, two Cuckoo Search variants and seven PSO algorithms. It is clear that the PSO family outperforms the rest. Surprisingly, one of the most efficient PSO algorithms is LPSO, which manages to converge to very good solutions for the stand alone calibration problem faster than more recently proposed PSO variants. However, it is the solutions provided by HEPSO that generalise better for the particular Figure 17 : Verification of the Sheffield model using input data from set S15 th and using the optimal parameter set based on (a) the S1. st data set and (b) the S8 th data set.. verification problem. The reasons for this result are unclear and are subject to further investigation. Future research will also focus on investigating different ways of incorporating the generalisation property of a solution directly into the problem formulation. An automatic way of identifying appropriate values for the weighting parameters in the objective function is also something that needs further development. In fact, the suggested problem formulation implies a multi-objective problem, aiming concurrently at error minimisation, FD number and parameter variance minimisation, and maximum optimal solution generalisation. Explicit multiobjective optimisation methods can provide an alternative approach to the one adopted here. A learning module able to reason about the quality of data used for calibration and the solution obtained is another viable research direction.. The overall objective is a system that combines modelling, optimisation and learning capabilities to automate the process of delivering relevant and up to date model parameter sets with minimum interference from the operator.

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Web-based electronic patient records for collaborative medical applications We developed a web-based system to interactively display electronic patient records (EPR), such as DICOM images, graphics, and structure reports and therapy records, for intranet and internet collaborative medical applications. This system has three major components, a C/S (client/server) architecture for EPR data acquisition and authoring, and a Web B/S architecture for data delivering. The Web viewer of this system integrates multi-media display modules and remote control module together to provide interactive EPR display and manipulation functions for collaborative applications. We have successfully used this system two times to provide teleconsultation for severe acute respiratory syndrome (SARS) patients in Shanghai Infection Hospital and Xinhua Hospital. During the consultation, both the physicians in infection control area and the experts outside the control area could use this system interactively to manipulate and navigate the EPR objects of the SARS patients to facilitate a more precise diagnosis. This paper gives a new approach to create and manage image-based EPR from actual patient records, and also presents a novel method to use Web technology and DICOM standard to build an open architecture for collaborative medical applications. The system can be used for both intranet and internet medical applications such as tele-diagnosis, teleconsultation, and distant learning. q During the past years, using PACS (picture archiving and communication system) diagnostic workstations and Web technologies as a means to access digital image data have been implemented with different architectures [1, 2] . Also, more and more multi-media medical documents or records are used in hospitals and medical community, and these documents usually are stored in different formats or systems. Most medical applications need to access these medical documents through intranet or internet. Also, there are a lot of collaborative medical applications needing to share or interactively exchange medical information through the networks [3, 4] .. Collaborative medical applications are often happened in some medical practices, procedures and education encounters. For example, local and remote doctors collaboratively discuss cases in telemedicine procedures [5, 6] . Medical students or residents study or learn cases from medical experts through network [7] . For infection diseases, physicians and experts in different departments or areas of an infection control hospital can study patient records collaboratively through networks without the concern of being infected. They can concentrate in case discussion with patient medical records combining with image manipulation, and show results to remote participants through the network.. For more difficult or complicated cases, the medical record usually contains medical images with other related records, which come from hospital information system (HIS) and other clinical information systems (CIS). For these reasons, the medical imaging informatics research and applications trends are to develop and build electronic patient record (EPR) with images for medical applications [8] , and this effort will benefit the hospitals and medical institutions on their collaborative healthcare activities.. In this paper, we first review our previously developed interactive teleradiology system architecture, and discussed its advantages and disadvantages in collaborative applications. Second, we present a new design of web-based interactive system architecture and its major components, which support EPR display and manipulation and operate in a central mode for collaborative applications. The new system can be integrated with PACS and other hospital clinical information systems, and provides a web interface to allow access to the EPR either through intranet or Internet for different applications. Third, we discuss the work and data flows of the web-based EPR system in collaborative applications. We also present the advantages of using the central operation mode for the collaboration comparing to the point-to-point mode. Finally, we give an example of the how the new web-based EPR system was used in collaborative application for SARS (Severe acute respiratory syndrome) diagnosis. Collaborative medical applications need to share or interactively to exchange medical information through the networks and most medical documents or records stored in different formats or systems. This paper presented a novel approach to design and develop a web-based electronic patient record system for collaborative medical applications. The electronic patient records supported by this system cover most DICOM image-based objects and medical records. This system has three major components, use a C/S architecture for EPR data acquisition and authoring, and a Web B/S architecture for data delivery. The web viewer of this system integrated multi-media display modules and remote control module together to provide interactive EPR display and manipulation functions for collaborative applications. The web-based architecture of the system makes the collaboration operation procedures much simpler and easier to the users. We have installed this system in Shanghai Infection Hospital and Shanghai Xinhua Hospital to provide teleconsultation services for SARS diagnosis between the SARS physicians and experts in May 2003. There were two consultation meetings held for SARS diagnosis between the Shanghai Infection Hospital and Xinhua Hospital during May 2003. The first consultation meeting was held using ADSL WAN, and the second consultation meeting was held using ATM WAN. There were 8 SARS patients consulted from the remote expert center, and total 2.73 Gb image data were transmitted from the Infection Hospital to Xinhua Hospital in the consultation activities. During the consultation meeting, the web-based EPR system provided bidirectional remote control functionality to both sides on the EPR data processing and manipulation, and synchronized their operations on the patient medical records so that it is easy for them to do the case analysis and management. The consultation results showed that this web-based EPR system could provide multi-sites interactive consultation services between SARS clinical physicians, so that radiologists and off-site experts did not have to be concerned with SARS infection. Also, the central collaborative operation mode simplified the consultation procedures in image and medical record delivery and display comparing to the point-to-point mode.. This paper also gives a new approach to create and manage image-based EPR from actual patient records, and also presents a novel method to use web technology and DICOM standard to build an open architecture for collaborative medical applications. The New web-based EPR system provides new method to enhance the value of interactive and collaborative studying of EPR for difficult cases, especially for SARS diagnosis. The on-time interactive communication features of the system can manipulate EPR objects which, in turn, can improve the efficiency and the quality of collaborative healthcare. The system can be used for both intranet and Internet medical applications such as tele-diagnosis, teleconsultation, and distant learning.

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O