Syntax-Aware Multi-Sense Word Embeddings for Deep Compositional Models of Meaning

Deep compositional models of meaning acting on distributional representations of words in order to produce vectors of larger text constituents are evolving to a popular area of NLP research. We detail a compositional distributional framework based on a rich form of word embeddings that aims at facilitating the interactions between words in the context of a sentence. Embeddings and composition layers are jointly learned against a generic objective that enhances the vectors with syntactic information from the surrounding context. Furthermore, each word is associated with a number of senses, the most plausible of which is selected dynamically during the composition process. We evaluate the produced vectors qualitatively and quantitatively with positive results. At the sentence level, the effectiveness of the framework is demonstrated on the MSRPar task, for which we report results within the state-of-the-art range.Comment: Accepted for presentation at EMNLP 201

Fifty years of Hoare's Logic

We present a history of Hoare's logic.Comment: 79 pages. To appear in Formal Aspects of Computin

Construction and Analysis of Petri Net Model for Distributed Cyber Physical Systems

A Distributed Cyber-Physical System (DCPS) composition poses challenges in determining its emergent behaviour. These challenges occur due to (1) the appearance of causal loops of information and energy flow through cyber and physical channels and (2) inherent non-determinism in the temporally ordered flow of events within independently evolving interacting processes of Constituent Systems (CSs). Hence, there is a need to construct a model of the envisaged schematic of DCPS composition for analysis and verification of its significant properties in the conceptual design stage of the system development life cycle. This paper presents a procedure to construct DCPS composition models in Petri net formalism using distributed abstractions. The model for each CS is obtained from elementary constructs using compositional operators. The interaction among CSs occurs through channels obtained by connecting send and receive constructs of two CSs participating in an interaction. The internal processing within a CS characterizing its primary function is abstracted in a generic passthrough construct. Representing these constructs with compositional operators results in the complete DCPS model in Petri net formalism. A toolchain with Reference net workshop (Renew) as an integrated Petri net editing and analysis platform is configured to support DCPS modelling, simulation and analysis. The Renew tool functionality has been enhanced with a plugin designed and developed by authors to facilitate the drawing of the distributed composition model. A low-level Petri net analysis (Lola) v2.0 plugin is employed to verify the Petri net and temporal properties of the modelled DCPS scenarios. The properties of the resultant model are verified using well-established algorithms to analyze Petri nets. Further, system properties specified using temporal logic can be verified using model-checking algorithms for Petri nets. A moderately complex scenario involving interactions among six CSs illustrates the presented approach