Logic programming and artificial neural networks in breast cancer detection

About 90% of breast cancers do not cause or are capable of producing death if detected at an early stage and treated properly. Indeed, it is still not known a specific cause for the illness. It may be not only a beginning, but also a set of associations that will determine the onset of the disease. Undeniably, there are some factors that seem to be associated with the boosted risk of the malady. Pondering the present study, different breast cancer risk assessment models where considered. It is our intention to develop a hybrid decision support system under a formal framework based on Logic Programming for knowledge representation and reasoning, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate the risk of developing breast cancer and the respective Degree-of-Confidence that one has on such a happening.

Genetic regulatory mechanisms by means of extended interactive Petri nets

In our work we have chosen to integrate formalism for knowledge representation with formalism for process representation as a way to specify and regulate the overall activity of a multi-cellular agent. The result of this approach is XP,N, another formalism, wherein a distributed system can be modeled as a collection of interrelated sub-nets sharing a common explicit control structure. Each sub-net represents a system of asynchronous concurrent threads modeled by a set of transitions. XP,N combines local state and control with interaction and hierarchy to achieve a high-level abstraction and to model the complex relationships between all the components of a distributed system. Viewed as a tool XP,N provides a carefully devised conflict resolution strategy that intentionally mimics the genetic regulatory mechanism used in an organic cell to select the next genes to process.

Methode und Anwendungen einer wissensorientierten Fabrikmodellierung

Factory planning, Factory modeling, Semantic Knowledge Representation, Digital Factory Planning, Digital Factory

MEVA-Ambiental: MEtodologia per a la Valoració de l'Aprenentatge. Centrada en l'educació ambiental

Aquest projecte abasta el disseny i el desenvolupament d’un model prototípic de Metodologia per a la Valoració de l’Aprenentatge Ambiental, a la qual anomenem “MEVA-Ambiental”. Per a fer possible aquesta fita ens hem basat en fonaments ontològics i constructivistes per representar i analitzar el coneixement a fi de poder quantificar l’Increment de Coneixement (IC). Per nosaltres l’IC esdevé un indicador socio-educatiu que ens servirà per a determinar l’efectivitat dels tallers d’educació ambiental en percentatge. En procedir d’aquesta manera, les qualificacions resultats poden es poden prendre com punt de partida per a desenvolupar estudis en el temps i comprendre com “s’ancora” el nou coneixement a l’estructura cognitiva dels aprenents. Més enllà del plantejament teòric de mètode, també proveïm la solució tècnica que mostra com n’és de funcional i d’aplicable la part empírica metodològica. A aquesta solució que hem anomenat “MEVA-Tool”, és una eina virtual que automatitza la recollida i tractament de dades amb una estructura dinàmica basada en “qüestionaris web” que han d’emplenar els estudiants, una “base de dades” que acumula la informació i en permet un filtratge selectiu, i més “Llibre Excel” que en fa el tractament informatiu, la representació gràfica dels resultats, l’anàlisi i conclusions.

Marcia J. Bates: El context i la interacció han de ser elements bàsics en els sistemes de recuperació de la informació

Entrevista a Marcia J. Bates a la University od California at Los Angeles i experta en sistemes de recuperació de la Informació orientats a l'usuari i en representació del contingut i accés per matèries. Es parla de l'evolució de les tecnologies i l'automatització de tasques que requereixen la capacitat de raonament de la persona, del comportament de l'usuari quan cerca per matèries, de la formació en competències en el maneig de la informació, de la necessitat del context en la indexació i la recuperació per matèries, i l'empatia en les relacions entre bibliotecaris i usuaris.

Estratègies en la presa de decisió d’una jugadora i el seu entrenador en el rugbi femení d’alt nivell = Estrategias en la toma de decisión de una jugadora y su entrenador en el rugby femenino de alto nivel

This research compared knowledge representation of a female rugby player and her coach concerning decision-making of the fly half in attack from second phase play. The current female England fly half and the England Women’s Rugby head coach analysed, from the fly half perspective, 15 sequences of the England v Spain match played during the 2002 Women’s Rugby World Cup in Barcelona. Protocol analysis of subjects’ verbal reports revealed that the player generated more overall concepts than the coach. The player’s analysis was based on condition-action statements related to goals. In contrast, the knowledge representation of the coach centred on conditions related to actions. Both subjects generated regulatory and do concepts in a similar way, with a majority of positive feedbacks. Knowledge structure of the player appeared to be more complex, but sophistication of concepts was similar for both subjects. Critical analysis of complete sequences viewed revealed a more severe self-assessment of the player compared with that of her coach. In conclusion, and despite the differences found between subjects, the player and her coach demonstrated possession of a similar pattern of decision-making strategies that could be due to a successful transmission of knowledge from the coach to his player

Semantics-supported cooperative learning for enhanced awareness

Awareness is required for supporting all forms of cooperation. In Computer Supported Collaborative Learning (CSCL), awareness can be used for enhancing collaborative opportunities across physical distances and in computer-mediated environments. Shared Knowledge Awareness (SKA) intends to increase the perception about the shared knowledge, students have in a collaborative learning scenario and also concerns the understanding that this group has about it. However, it is very difficult to produce accurate awareness indicators based on informal message exchange among the participants. Therefore, we propose a semantic system for cooperation that makes use of formal methods for knowledge representation based on semantic web technologies. From these semantics-enhanced repository and messages, it could be easier to compute more accurate awareness.

Semantic and fuzzy modelling for human behaviour recognition in smart spaces : a case study on ambient assisted living.

Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.

Attribute exploration with background implications and exceptions

Implications between attributes can represent knowledge about objects in a specified context. This knowledge representation is especially useful when it is not possible to list all specified objects. Attribute exploration is a tool of formal concept analysis that supports the acquisition of this knowledge. For a specified context this interactive procedure determines a miminal list of valid implications between attributes of this context together with a list of objects which are counterexamples for all implications not valid in the context. This paper describes how the exploration can be modified such that it determines a mimimal set of implications that fills the gap between previously given implications (called background implications) and all valid implications. The list of implications can be simplified further if exceptions are allowed for the implications.

Intelligent structuring and reducing of association rules with formal concept analysis

Association rules are used to investigate large databases. The analyst is usually confronted with large lists of such rules and has to find the most relevant ones for his purpose. Based on results about knowledge representation within the theoretical framework of Formal Concept Analysis, we present relatively small bases for association rules from which all rules can be deduced. We also provide algorithms for their calculation.

Off to new shores

In the last years, the main orientation of Formal Concept Analysis (FCA) has turned from mathematics towards computer science. This article provides a review of this new orientation and analyzes why and how FCA and computer science attracted each other. It discusses FCA as a knowledge representation formalism using five knowledge representation principles provided by Davis, Shrobe, and Szolovits [DSS93]. It then studies how and why mathematics-based researchers got attracted by computer science. We will argue for continuing this trend by integrating the two research areas FCA and Ontology Engineering. The second part of the article discusses three lines of research which witness the new orientation of Formal Concept Analysis: FCA as a conceptual clustering technique and its application for supporting the merging of ontologies; the efficient computation of association rules and the structuring of the results; and the visualization and management of conceptual hierarchies and ontologies including its application in an email management system.

Automated Reasoning About Classical Mechanics

In recent years, researchers in artificial intelligence have become interested in replicating human physical reasoning talents in computers. One of the most important skills in this area is predicting how physical systems will behave. This thesis discusses an implemented program that generates algebraic descriptions of how systems of rigid bodies evolve over time. Discussion about the design of this program identifies a physical reasoning paradigm and knowledge representation approach based on mathematical model construction and algebraic reasoning. This paradigm offers several advantages over methods that have become popular in the field, and seems promising for reasoning about a wide variety of classical mechanics problems.

WAIS seminar: Ontologies on the Web: An Alternative Model

Wednesday 2nd April 2014 Speaker(s): Stefan Decker Time: 02/04/2014 11:00-11:50 Location: B2/1083 File size: 897 Mb Abstract Ontologies have been promoted and used for knowledge sharing. Several models for representing ontologies have been developed in the Knowledge Representation field, in particular associated with the Semantic Web. In my talk I will summarise developments so far, and will argue that the currently advocated approaches miss certain basic properties of current distributed information sharing infrastructures (read: the Web and the Internet). I will sketch an alternative model aiming to support knowledge sharing and re-use on a global basis.