Argument Structure: Representation and Processing

ضرب‌کننده و ضرب‌جمع‌کننده پیمانه 2n+1 برای پردازنده سیگنال دیجیتال

Nowadays, digital signal processors (DSPs) are appropriate choices for real-time image and video processing in embedded multimedia applications not only due to their superior signal processing performance, but also of the high levels of integration and very low-power consumption. Filtering which consists of multiple addition and multiplication operations, is one of the most fundamental operatio...

The Effect of Dynamic Assessment of Toulmin Model through Teacher- and Collective-Scaffolding on Argument Structure and Argumentative Writing Achievement of Iranian EFL Learners

Considering the paramount importance of writing logical arguments for college students, this study investigated the effect of dynamic assessment (DA) of Toulmin model through teacher- and collective-scaffolding on argument structure and overall quality of argumentative essays of Iranian EFL university learners. In so doing, 45 male and female Iranian EFL learners taking part in the study were r...

The Effect of Semantic Transfer on Iranian EFL Learners’ Lexical Representation and Processing

Deblocking Joint Photographic Experts Group Compressed Images via Self-learning Sparse Representation

JPEG is one of the most widely used image compression method, but it causes annoying blocking artifacts at low bit-rates. Sparse representation is an efficient technique which can solve many inverse problems in image processing applications such as denoising and deblocking. In this paper, a post-processing method is proposed for reducing JPEG blocking effects via sparse representation. In this ...

Voice-based Age and Gender Recognition using Training Generative Sparse Model

Abstract: Gender recognition and age detection are important problems in telephone speech processing to investigate the identity of an individual using voice characteristics. In this paper a new gender and age recognition system is introduced based on generative incoherent models learned using sparse non-negative matrix factorization and atom correction post-processing method. Similar to genera...

Is Structure Necessary for Modeling Argument Expectations in Distributional Semantics?

Despite the number of NLP studies dedicated to thematic fit estimation, little attention has been paid to the related task of composing and updating verb argument expectations. The few exceptions have mostly modeled this phenomenon with structured distributional models, implicitly assuming a similarly structured representation of events. Recent experimental evidence, however, suggests that huma...