Search results for "Encoding"
showing 10 items of 134 documents
Smoothed Spherical Truncation based on Fuzzy Membership Functions: Application to the Molecular Encoding.
2019
A novel spherical truncation method, based on fuzzy membership functions, is introduced to truncate interatomic (or interaminoacid) relations according to smoothing values computed from fuzzy membership degrees. In this method, the molecules are circumscribed into a sphere, so that the geometric centers of the molecules are the centers of the spheres. The fuzzy membership degree of each atom (or aminoacid) is computed from its distance with respect to the geometric center of the molecule, by using a fuzzy membership function. So, the smoothing value to be applied in the truncation of a relation (or interaction) is computed by averaging the fuzzy membership degrees of the atoms (or aminoacid…
Arabidopsis RCD1 coordinates chloroplast and mitochondrial functions through interaction with ANAC transcription factors
2019
Reactive oxygen species (ROS)-dependent signaling pathways from chloroplasts and mitochondria merge at the nuclear protein RADICAL-INDUCED CELL DEATH1 (RCD1). RCD1 interacts in vivo and suppresses the activity of the transcription factors ANAC013 and ANAC017, which mediate a ROS-related retrograde signal originating from mitochondrial complex III. Inactivation of RCD1 leads to increased expression of mitochondrial dysfunction stimulon (MDS) genes regulated by ANAC013 and ANAC017. Accumulating MDS gene products, including alternative oxidases (AOXs), affect redox status of the chloroplasts, leading to changes in chloroplast ROS processing and increased protection of photosynthetic apparatus.…
Massively Parallel ANS Decoding on GPUs
2019
In recent years, graphics processors have enabled significant advances in the fields of big data and streamed deep learning. In order to keep control of rapidly growing amounts of data and to achieve sufficient throughput rates, compression features are a key part of many applications including popular deep learning pipelines. However, as most of the respective APIs rely on CPU-based preprocessing for decoding, data decompression frequently becomes a bottleneck in accelerated compute systems. This establishes the need for efficient GPU-based solutions for decompression. Asymmetric numeral systems (ANS) represent a modern approach to entropy coding, combining superior compression results wit…
The two-stage process in visual working memory consolidation
2019
AbstractTwo hypotheses have been proposed to explain the formation manner for visual working memory (VWM) representations during the consolidation process: an all-or-none process hypothesis and a coarse-to-fine process hypothesis. However, neither the all-or-none process hypothesis nor the coarse-to-fine process hypothesis can stipulate clearly how VWM representations are formed during the consolidation process. In the current study, we propose a two-stage process hypothesis to reconcile these hypotheses. The two-stage process hypothesis suggests that the consolidation of coarse information is an all-or-none process in the early consolidation stage, while the consolidation of detailed infor…
Measuring the clustering effect of BWT via RLE
2017
Abstract The Burrows–Wheeler Transform (BWT) is a reversible transformation on which are based several text compressors and many other tools used in Bioinformatics and Computational Biology. The BWT is not actually a compressor, but a transformation that performs a context-dependent permutation of the letters of the input text that often create runs of equal letters (clusters) longer than the ones in the original text, usually referred to as the “clustering effect” of BWT. In particular, from a combinatorial point of view, great attention has been given to the case in which the BWT produces the fewest number of clusters (cf. [5] , [16] , [21] , [23] ). In this paper we are concerned about t…
Taxonomic Classification for Living Organisms Using Convolutional Neural Networks
2017
Taxonomic classification has a wide-range of applications such as finding out more about evolutionary history. Compared to the estimated number of organisms that nature harbors, humanity does not have a thorough comprehension of to which specific classes they belong. The classification of living organisms can be done in many machine learning techniques. However, in this study, this is performed using convolutional neural networks. Moreover, a DNA encoding technique is incorporated in the algorithm to increase performance and avoid misclassifications. The algorithm proposed outperformed the state of the art algorithms in terms of accuracy and sensitivity, which illustrates a high potential f…
Why Digital Games Can Be Advantageous in Vocabulary Learning
2021
Vocabulary learning is an integral part of language learning; however, it is difficult. Although there are many techniques proposed for vocabulary learning and teaching, researchers still strive to find effective methods. Recently, digital games have shown potentials in enhancing vocabulary acquisition. A majority of studies in digital game-based vocabulary learning (DGBVL) literature investigate the effectiveness of DGBVL tasks. In other words, there are enough answers to what questions in DGBVL literature whereas why questions are rarely answered. Finding such answers help us learn more about the structure of the DGBVL tasks and their effects on vocabulary learning. Hence, to achieve this…
Optical-data storage-readout technique based on fractal encrypting masks
2009
We propose the use of fractal structured diffractive masks as keys in secure storage-readout systems. A joint transform correlator based on a photorefractive crystal in the Fourier domain is implemented to perform encryption and decryption. We discuss the advantages of encrypting information using this kind of deterministic keys in comparison to conventional random phase masks. Preliminary experimental results are presented to demonstrate the effectiveness of the proposed system.
Phonological-Lexical Feedback during Early Abstract Encoding: The Case of Deaf Readers.
2016
In the masked priming technique, physical identity between prime and target enjoys an advantage over nominal identity in nonwords (GEDA-GEDA faster than geda-GEDA). However, nominal identity overrides physical identity in words (e.g., REAL-REAL similar to real-REAL). Here we tested whether the lack of an advantage of the physical identity condition for words was due to top-down feedback from phonological-lexical information. We examined this issue with deaf readers, as their phonological representations are not as fully developed as in hearing readers. Results revealed that physical identity enjoyed a processing advantage over nominal identity not only in nonwords but also in words (GEDA-GE…
Early use of phonological codes in deaf readers: An ERP study.
2017
Previous studies suggest that deaf readers use phonological information of words when it is explicitly demanded by the task itself. However, whether phonological encoding is automatic remains controversial. The present experiment examined whether adult congenitally deaf readers show evidence of automatic use of phonological information during visual word recognition. In an ERP masked priming lexical decision experiment, deaf participants responded to target words preceded by a pseudohomophone (koral - CORAL) or an orthographic control prime (toral - CORAL). Responses were faster for the pseudohomophone than for the orthographic control condition. The N250 and N400 amplitudes were reduced fo…