Sharif Digital Repository

In a series of essays, beginning with this article, we are going to develop a new formulation of microphenomena based on the principles of reality and causality. The new theory provides us with a new depiction of microphenomena assuming a unified concept of information, matter and energy. So, we suppose that in a definite microphysical context (including other interacting particles), each particle is enfolded by a probability field whose existence is contingent on the existence of the particle, but it can locally affect the physical status of the particle in a context-dependent manner. The dynamics of the whole particle-field system obeys deterministic equations in a manner such that when... 

As Gregory Bateson, the British social scientists, once said "You can't live without an eraser", the process of learning is not a unidirectional way toward accumulation of knowledge, rather, organizations should critically evaluate the value of their knowledge and if necessary, actively forget no-longer-useful knowledge. A brief review of related literature shows that the concept of knowledge active forgetting (KAF) is a crucial aspect of organizational learning and knowledge management. However, many aspects of this topic deserve more attention by researchers. The main gap in the literature seems to be related to the linkage between peculiar aspects of knowledge (such as stickiness, context... 

In this paper, the problem of spatial error concealment for real-time applications is addressed. The proposed method can be categorized in exemplar-based error concealment approaches. In this category, a patch of corrupted pixels are replaced by another patch of the image that contains correct pixels. For splitting the erroneous block to different patches, a novel context-dependent exemplar-based algorithm based on a previously proposed segmentation method is proposed. The capability of the proposed method for concealment in diverse image regions is depicted. Our detailed conducted experiments show that the proposed method outperforms the state-of-the-art spatial error concealment methods in... 

Decision tree-clustered context-dependent hidden semi-Markov models (HSMMs) are typically used in statistical parametric speech synthesis to represent probability densities of acoustic features given contextual factors. This paper addresses three major limitations of this decision tree-based structure: (i) The decision tree structure lacks adequate context generalization. (ii) It is unable to express complex context dependencies. (iii) Parameters generated from this structure represent sudden transitions between adjacent states. In order to alleviate the above limitations, many former papers applied multiple decision trees with an additive assumption over those trees. Similarly, the current... 

Reo is an exogenous coordination language for synchronizing components participating in a component-based system. In this paper we provide a verification framework for model checking of Reo connectors. The proposed framework applies an extension of Büchi automata as the operational semantic model for Reo connectors and a record-based extension of linear time temporal logic (LTL) for expressing properties. Several aspects of Reo connectors, specially synchronization, context dependencies and fairness constraints, are addressed by this model checker due to its supported underlying model. The main ideas behind this implementation are to introduce a symbolic representation for the main elements... 

We present our work on end-to-end training of acoustic models using the lattice-free maximum mutual information (LF-MMI) objective function in the context of hidden Markov models. By end-to-end training, we mean flat-start training of a single DNN in one stage without using any previously trained models, forced alignments, or building state-tying decision trees. We use full biphones to enable context-dependent modeling without trees, and show that our end-to-end LF-MMI approach can achieve comparable results to regular LF-MMI on well-known large vocabulary tasks. We also compare with other end-to-end methods such as CTC in character-based and lexicon-free settings and show 5 to 25 percent... 

Reo is a connector language for the exogenous composition and orchestration of components in a software system. An operational semantics of Reo connectors can be given in terms of Büchi automata over a suitable alphabet of records, capturing both synchronization and context dependency requirements. In this paper, we define an action based linear time temporal logic for expressing properties of Reo connectors. Formulas can be synthesized into Büchi automata representing Reo connectors, thus leading to an automata based model checking algorithm. By generalizing standard automata based model checking algorithms for linear time temporal logic, we give an efficient on-the-fly algorithm for the... 

Reo is an exogenous coordination language for synthesizing components participating in a component-based system. The notion of Bchi automaton over streams of records (BAR for short) is a proposed operational semantics for Reo that covers several aspects of coordination strategies such as synchronization, context dependencies and fairness constraints. In this paper and for the purpose of modeling real-time coordination systems specified by Reo, we present a timed version of BARs as the acceptors of timed streams of records. We show that timed BAR and its streams of records based semantics are more standard and also more expressive than timed constraint automaton which is the first proposed...