Moffett and rhetoric

This examination of Moffett's contribution to a theory of school English concentrates on his understanding of rhetoric. It is suggested that the impetus for Teaching the Universe of Discourse is dialectical: he was running against currents in English teaching at the time that were literary and technical, as well as the specific practices of sentence combining and embedding. His introduction of rhetoric into debates about school English was a key move, as rhetoric had been seen by American contemporaries as related to higher education and public discourse (and drawing on classical models). Moffett's more generous notion of rhetoric as the ‘arts of discourse’ helped him chart a ‘larger rhetoric of behaviour’ and map out his curriculum and development model. It is a rhetoric that moves beyond the definition of the ‘art of persuasion’ to one based in drama, dialogue and dialectic

Model the System from Adversary Viewpoint: Threats Identification and Modeling

Security attacks are hard to understand, often expressed with unfriendly and limited details, making it difficult for security experts and for security analysts to create intelligible security specifications. For instance, to explain Why (attack objective), What (i.e., system assets, goals, etc.), and How (attack method), adversary achieved his attack goals. We introduce in this paper a security attack meta-model for our SysML-Sec framework, developed to improve the threat identification and modeling through the explicit representation of security concerns with knowledge representation techniques. Our proposed meta-model enables the specification of these concerns through ontological concepts which define the semantics of the security artifacts and introduced using SysML-Sec diagrams. This meta-model also enables representing the relationships that tie several such concepts together. This representation is then used for reasoning about the knowledge introduced by system designers as well as security experts through the graphical environment of the SysML-Sec framework.Comment: In Proceedings AIDP 2014, arXiv:1410.322

Protein sequence classification using feature hashing

Recent advances in next-generation sequencing technologies have resulted in an exponential increase in the rate at which protein sequence data are being acquired. The k-gram feature representation, commonly used for protein sequence classification, usually results in prohibitively high dimensional input spaces, for large values of k. Applying data mining algorithms to these input spaces may be intractable due to the large number of dimensions. Hence, using dimensionality reduction techniques can be crucial for the performance and the complexity of the learning algorithms. In this paper, we study the applicability of feature hashing to protein sequence classification, where the original high-dimensional space is "reduced" by hashing the features into a low-dimensional space, using a hash function, i.e., by mapping features into hash keys, where multiple features can be mapped (at random) to the same hash key, and "aggregating" their counts. We compare feature hashing with the "bag of k-grams" approach. Our results show that feature hashing is an effective approach to reducing dimensionality on protein sequence classification tasks

More on the Relations among Categorization, Merge and Labeling, and Their Nature

More on the Relations among More on the Relations among Categorization, Merge and Labeling, and Their Nature, Merge and Labeling, and Their Natur

A graph-based mathematical morphology reader

This survey paper aims at providing a "literary" anthology of mathematical morphology on graphs. It describes in the English language many ideas stemming from a large number of different papers, hence providing a unified view of an active and diverse field of research

COLAB : a hybrid knowledge representation and compilation laboratory

Knowledge bases for real-world domains such as mechanical engineering require expressive and efficient representation and processing tools. We pursue a declarative-compilative approach to knowledge engineering. While Horn logic (as implemented in PROLOG) is well-suited for representing relational clauses, other kinds of declarative knowledge call for hybrid extensions: functional dependencies and higher-order knowledge should be modeled directly. Forward (bottom-up) reasoning should be integrated with backward (top-down) reasoning. Constraint propagation should be used wherever possible instead of search-intensive resolution. Taxonomic knowledge should be classified into an intuitive subsumption hierarchy. Our LISP-based tools provide direct translators of these declarative representations into abstract machines such as an extended Warren Abstract Machine (WAM) and specialized inference engines that are interfaced to each other. More importantly, we provide source-to-source transformers between various knowledge types, both for user convenience and machine efficiency. These formalisms with their translators and transformers have been developed as part of COLAB, a compilation laboratory for studying what we call, respectively, "vertical\u27; and "horizontal\u27; compilation of knowledge, as well as for exploring the synergetic collaboration of the knowledge representation formalisms. A case study in the realm of mechanical engineering has been an important driving force behind the development of COLAB. It will be used as the source of examples throughout the paper when discussing the enhanced formalisms, the hybrid representation architecture, and the compilers

Formalizing enrichment mechanisms for bibliographic ontologies in the Semantic Web

This paper presents an analysis of current limitations to the reuse of bibliographic data in the Semantic Web and a research proposal towards solutions to overcome them. The limitations identified derive from the insufficient convergence between existing bibliographic ontologies and the principles and techniques of linked open data (LOD); lack of a common conceptual framework for a diversity of standards often used together; reduced use of links to external vocabularies and absence of Semantic Web mechanisms to formalize relationships between vocabularies, as well as limitations of Semantic Web languages for the requirements of bibliographic data interoperability. A proposal is advanced to investigate the hypothesis of creating a reference model and specifying a superontology to overcome the misalignments found, as well as the use of SHACL (Shapes Constraint Language) to solve current limitations of RDF languages.info:eu-repo/semantics/acceptedVersio

Artificial Intelligence-The Emerging Technology

Artificial Intelligence (AI), once considered as an obscure branch of computer science, is now having a growing number of adherents in a wide variety of fields. AI is particularly useful for combat automation in defence. The combined works of computer scientists and technologists and cognitive scientists have brought out for intelligent information processing knowledge is the key factor. In the last few years, AI has been tried out with a high degree of success in certain areas such as the Expert Systems and the Computer Vision Systems. Both these have great potential in target classification and identification, information fusion, multiradar Air Defence Network, C2 (Command andControl) operations etc. in defence