Domain-specific computing is one approach to greatly improving server performance by specially designing a server architecture for a particular application domain. A good way to implement such an approach is to use a field-programmable gate array (FPGA), a commodity device in which processing units and memory blocks can be configured depending on the application requirements. We have developed ...

normal 0 false false false en-us x-none fa background: the angular dependency of response for tld cards may cause deviation  from its true value on the results of environmental dosimetry, since tlds may  be exposed to radiation at different angles of incidence from the surrounding area. objective: a 3d setting of tld cards has been calibrated isotropically in a standard  radiation field to eval...

We would like to draw attention to Hidden Markov Tree Models (HMTM), which are to our knowledge still unexploited in the field of Computational Linguistics, in spite of highly successful Hidden Markov (Chain) Models. In dependency trees, the independence assumptions made by HMTM correspond to the intuition of linguistic dependency. Therefore we suggest to use HMTM and tree-modified Viterbi algo...

Spatial and temporal variation in interactions among plants, other species and the abiotic environment create context-dependency in vegetation pattern. We argue that we can enhance understanding of context-dependency by being more explicit about the kinds of direct interactions that occur among more than two living and non-living entities (i. e., third through nth parties) and formalizing how t...

The role of oral corrective feedback has been investigated by SLA researchers from various perspectives. Focusing on Iranian EFL context, the present study aimed to explore the role of receiving corrective feedback in the learning of English grammatical structures. It also probed the association between the type of corrective feedback and EFL learners’ learning styles. This was an experimental ...

In this paper, we develop a novel approach to aspect term extraction based on unsupervised learning of distributed representations of words and dependency paths. The basic idea is to connect two words (w1 and w2) with the dependency path (r) between them in the embedding space. Specifically, our method optimizes the objective w1 + r ≈ w2 in the low-dimensional space, where the multihop dependen...

Named Entity Recognition is an information extraction technique that identifies name entities in a text. Three popular methods have been conventionally used namely: rule-based, machine-learning-based and hybrid of them to extract named entities from a text. Machine-learning-based methods have good performance in the Persian language if they are trained with good features. To get good performanc...