Design and Deployment of Expressive and Correct Web of Things Applications

Consumer Internet of Things (IoT) applications are largely built through end-user programming in the form of event-action rules. Although end-user tools help simplify the building of IoT applications to a large extent, there are still challenges in developing expressive applications in a simple yet correct fashion. In this context, we propose a formal development framework based on the Web of Things specification. An application is defined using a composition language that allows users to compose the basic event-action rules to express complex scenarios. It is transformed into a formal specification that serves as the input for formal analysis, where the application is checked for functional and quantitative properties at design time using model checking techniques. Once the application is validated, it can be deployed and the rules are executed following the composition language semantics. We have implemented these proposals in a tool built on top of the Mozilla WebThings platform. The steps from design to deployment were validated on real-world applications.

Challenge Problems for a Theory of Degree Multiplication (with partial answer key)

This paper offers a theory of degree multiplication in natural language semantics. Motivation for the development such a theory comes from proportional readings of quantity words and rate expressions such as miles per hour. After laying out a set of ‘challenge problems’ that any good theory of degree multiplication should be able to handle, I set about solving them, borrowing mathematical tools from quantity calculus. These algebraic foundations are integrated into a compositional Montagovian framework, yielding a system that can solve, or partially solve, some of the problems.

Language Semantics Interpretation with an Interaction-Based Recurrent Neural Network

Text classification is a fundamental language task in Natural Language Processing. A variety of sequential models are capable of making good predictions, yet there is a lack of connection between language semantics and prediction results. This paper proposes a novel influence score (I-score), a greedy search algorithm, called Backward Dropping Algorithm (BDA), and a novel feature engineering technique called the “dagger technique”. First, the paper proposes to use the novel influence score (I-score) to detect and search for the important language semantics in text documents that are useful for making good predictions in text classification tasks. Next, a greedy search algorithm, called the Backward Dropping Algorithm, is proposed to handle long-term dependencies in the dataset. Moreover, the paper proposes a novel engineering technique called the “dagger technique” that fully preserves the relationship between the explanatory variable and the response variable. The proposed techniques can be further generalized into any feed-forward Artificial Neural Networks (ANNs) and Convolutional Neural Networks (CNNs), and any neural network. A real-world application on the Internet Movie Database (IMDB) is used and the proposed methods are applied to improve prediction performance with an 81% error reduction compared to other popular peers if I-score and “dagger technique” are not implemented.

Modular, compositional, and executable formal semantics for LLVM IR

This paper presents a novel formal semantics, mechanized in Coq, for a large, sequential subset of the LLVM IR. In contrast to previous approaches, which use relationally-specified operational semantics, this new semantics is based on monadic interpretation of interaction trees, a structure that provides a more compositional approach to defining language semantics while retaining the ability to extract an executable interpreter. Our semantics handles many of the LLVM IR's non-trivial language features and is constructed modularly in terms of event handlers, including those that deal with nondeterminism in the specification. We show how this semantics admits compositional reasoning principles derived from the interaction trees equational theory of weak bisimulation, which we extend here to better deal with nondeterminism, and we use them to prove that the extracted reference interpreter faithfully refines the semantic model. We validate the correctness of the semantics by evaluating it on unit tests and LLVM IR programs generated by HELIX.

Is Aristotle the Forefather of Informal Logic?

I argue that Aristotle takes a ‘natural language semantics’ approach to logic, which is consistent with the general attitudes one finds in informal logic today. Although his position is complex, Aristotle emphasizes the intensional rather than the extensional side of argument evaluation. He does not take a truth-functional approach to semantics, but an approach that elucidates the illative mechanism through an understanding of natures. This comes close to what informal logicians insist on. The informal logic movement was, to a very large extent, a Canadian initiative, prominently featuring authors such as Johnson, Blair, Govier, and many others.

exture Oriented Scene Generation from Natural Language Text Description using 3D Coloured Objects

To understand language, we need an understanding of the world around us. Language describes the world and provides symbols with which we represent meaning. Still, much knowledge about the world is so obvious that it is rarely explicitly stated. It is uncommon for people to state that chairs are usually on the floor and upright, and that you usually eat a cake from a plate on a table. Knowledge of such common facts provides the context within which people communicate with language. Therefore, to create practical systems that can interact with the world and communicate with people, we need to leverage such knowledge to interpret language in context. Scene generation can be used to achieve an ability to generate 3D scenes on basis of text description. A model capable of learning natural language semantics or interesting pattern to generate abstract idea behind scene composition is interesting [1].Scene generation from text involves several fields like NLP, artificial intelligence, computer vision and machine learning. This paper focuses on optimally arranging objects in a room with focus on the orientation of the objects with respect to the floor, wall and ceiling of a room along with textures. Our model suggest a novel framework which can be used as a tool to generate scene where anyone without 3D Modeling.

Generative Linguistics Meets Normative Inferentialism

This is the second installment of a two-part essay. Limitations of space prevented the publication of the full essay in a previous issue of the Journal (Pereplyotchik 2020). My overall goal is to outline a strategy for integrating generative linguistics with a broadly pragmatist approach to meaning and communication. Two immensely useful guides in this venture are Robert Brandom and Paul Pietroski. Squarely in the Chomskyan tradition, Pietroski’s recent book, Conjoining Meanings, offers an approach to natural-language semantics that rejects foundational assumptions widely held amongst philosophers and linguists. In particular, he argues against extensionalism—the view that meanings are (or determine) truth and satisfaction conditions. Having arrived at the same conclusion by way of Brandom’s deflationist account of truth and reference, I’ll argue that both theorists have important contributions to make to a broader anti-extensionalist approach to language. Part 1 of the essay was largely exegetical, laying out what I see as the core aspects of Brandom’s normative inferentialism (1) and Pietroski’s naturalistic semantics (2). Now, in Part 2, I argue that there are many convergences between these two theoretical frameworks and, contrary to first appearances, very few points of substantive disagreement between them. If the integration strategy that I propose is correct, then what appear to be sharply contrasting commitments are better seen as interrelated verbal differences that come down to different—but complementary—explanatory goals. The residual disputes are, however, stubborn. I end by discussing how to square Pietroski’s commitment to predicativism with Brandom’s argument that a predicativist language is in principle incapable of expressing ordinary conditionals.

Conceptual Graphs and Terminological Idiosyncrasy in UNCLOS and CBD

Do two conventions of international environmental law necessarily endow the same word with the same meaning? A single counterexample is enough to answer in the negative: this is the case of the term “resource” in the United Nations Convention on the Law of the Sea (UNCLOS) and the Convention on Biological Diversity (CBD). Beyond this result, we tackle the questions, raised by the method of analysis implemented, about the semantics of legal texts, a source of interpretative flexibility but also of cognitive amalgamations and confusions of various types. A conceptual graph is associated with each proposition or sentence comprising the term “resource.” Some expressions, especially those of a deontic nature and noun phrases naming a group of interrelated entities or a fact, are encoded in nested graphs. The scope of a term is revealed by the neighbourhood of its uses. Neighbouring expressions, positioned along the paths of conceptual graphs, are ranked owing to their distance from the target expression. Then the neighbours the most contributing to the distributional meaning of the targets are classified in a coarse taxonomy, providing basic ontological traits to “resource” and related expressions in each convention. Although the two conventions rely on the same language, the weak overlap of their respective neighbourhoods of the term “resource” and associated expressions and their contrasted ontological anchorages highlight idiosyncratic meanings and, consequently, divergent orientations and understandings regarding the protection and conservation of resources, especially of living resources. Thus, the complexity of legal texts operates both in the gap between language semantics and cognitive understanding of the concepts used, and in the interpretative flexibility and opportunities for confusion that the texts offer but that the elementary operations of formalisation allow to deconstruct and clarify.

The South African Perspective of the Impact of Language on the Delivery of Healthcare Services

Despite its essentiality, spoken languages continue to pose severe challenges within the South African health facilities, which can be attributed to the country's adaptation of 11 official languages. Some of the challenges can be attributed to the fact that the limits to an individual's language are commensurate to the limits to an individual's real-life world and meaning, which are often influenced by semantics. The objectives of this study was to establish the factors that influence spoken languages, and how the semantics in the languages can be translated from local dialects to English by using mobile systems. The interpretivist approach was applied in the study. Data was collected through semi-structured interview technique. The actor-network theory was used as a lens to guide the analysis of the data. From the analysis, the following factors—heterogeneity of networks, bilingualism, healthcare facility, and information engine—were found to influence language semantics in South African healthcare. Based on the findings, a framework was developed that can be used to understand how language semantics influence healthcare services in the country. Thus, the study can be of interest to healthcare practitioners, language specialists for translation purposes, and IT experts for support and enablement.