scholarly journals Enhancing Detection of SSMVEP Induced by Action Observation Stimuli Based on Task-Related Component Analysis

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5269
Author(s):  
Xin Zhang ◽  
Wensheng Hou ◽  
Xiaoying Wu ◽  
Lin Chen ◽  
Ning Jiang
Keyword(s):  
Recognition Performance ◽  
Action Observation ◽  
Component Analysis ◽  
Spatial Filters ◽  
Interesting Phenomenon ◽  
Speed Up ◽  
Short Stimulus ◽  
First Time ◽  
Complex Modulation ◽  
Short Stimulus Duration

Action observation (AO)-based brain-computer interface (BCI) is an important technology in stroke rehabilitation training. It has the advantage of simultaneously inducing steady-state motion visual evoked potential (SSMVEP) and activating sensorimotor rhythm. Moreover, SSMVEP could be utilized to perform classification. However, SSMVEP is composed of complex modulation frequencies. Traditional canonical correlation analysis (CCA) suffers from poor recognition performance in identifying those modulation frequencies at short stimulus duration. To address this issue, task-related component analysis (TRCA) was utilized to deal with SSMVEP for the first time. An interesting phenomenon was found: different modulated frequencies in SSMVEP distributed in different task-related components. On this basis, a multi-component TRCA method was proposed. All the significant task-related components were utilized to construct multiple spatial filters to enhance the detection of SSMVEP. Further, a combination of TRCA and CCA was proposed to utilize both advantages. Results showed that the accuracies using the proposed methods were significant higher than that using CCA at all window lengths and significantly higher than that using ensemble-TRCA at short window lengths (≤2 s). Therefore, the proposed methods further validate the induced modulation frequencies and will speed up the application of the AO-based BCI in rehabilitation.

“Little Trio” for clarinet, bassoon and piano

2018 ◽  
pp. 75-79
Author(s):  
N. Yakovchuk
Keyword(s):  
Chamber Music ◽  
Instrumental Music ◽  
Instrumental Ensemble ◽  
Interesting Phenomenon ◽  
Theoretical Understanding ◽  
Classical Traditions ◽  
And Performance ◽  
Instrumental Ensembles ◽  
Written Compositions ◽  
First Time

The chamber-instrumental ensemble music in the Ukrainian musical culture of the last third of the 20th and the beginning of the 21st centuries occupies one of the leading places and is characterized by powerful processes in its development. Such circumstances caused the Ukrainian musicologist interests to the problems of chamber-instrumental music creativity and performance. There are appeared researches in the field of theory, history and performance problems covering the most important questions like chamber music definitions, specific genre issues, the growing function of piano in the Ukrainian chamber music, the increasing questions of technique and timbre importance of modern instrumental ensembles. In the significant multifaceted creative work of contemporary Ukrainian composer, Oleksandr Yakovchuk, the genre of chamber instrumental ensemble music represents a complex and interesting phenomenon. Original and skillfully written compositions reflect artistic world of the composer of postmodern time and gained recognition in music life of Ukraine and beyond. These works are highly appreciated in performing practice of our days. The purpose of the article is to analyze the work — “Little Trio” for clarinet, bassoon and piano (1980), which has the signs of neoclassical tendency in the composer’s style. The methodological basis of this research is a comprehensive approach in theoretical understanding of the subject of research (the methods of textology, source study as well as the method of interviewing the author were used). The scientific novelty of this article is in the priority of its main provisions, since the “Little Trio” entered the scientific circulation for the first time. The three-movement “Little Trio” (1980) is notable for the light feeling of timbre colours and the shape clarity. The Ist movement — Allegretto giocoso — is written in a sonata form following all classical traditions. Quite interesting are the two monologues of clarinet and bassoon from the IInd movement, they represent very modern line in Ukrainian chamber music — the possibility of sincere confession which comes through the solo cadence. In the IIIrd movement, the composer took advantage from the folk Ukrainian dance “hopak” using the rhythm of it and creating dance character of the Final.

Palm Vein Recognition Based on Independent Component Analysis

2013 ◽  
Vol 333-335 ◽  
pp. 1106-1109
Author(s):  
Wei Wu
Keyword(s):  
Pattern Recognition ◽  
Independent Component Analysis ◽  
Euclidean Distance ◽  
Recognition Performance ◽  
Component Analysis ◽  
Independent Component ◽  
Experimental Results ◽  
Vein Pattern ◽  
Vein Recognition ◽  
Palm Vein

Palm vein pattern recognition is one of the newest biometric techniques researched today. This paper proposes project the palm vein image matrix based on independent component analysis directly, then calculates the Euclidean distance of the projection matrix, seeks the nearest distance for classification. The experiment has been done in a self-build palm vein database. Experimental results show that the algorithm of independent component analysis is suitable for palm vein recognition and the recognition performance is practical.

Fast Solution of Transient Elastohydrodynamic Line Contact Problems Using the Trajectory Piecewise Linear Approach

2015 ◽  
Vol 138 (1) ◽  
Author(s):  
Daniel Maier ◽  
Corinna Hager ◽  
Hartmut Hetzler ◽  
Nicolas Fillot ◽  
Philippe Vergne ◽  
...  
Keyword(s):  
Piecewise Linear ◽  
Contact Problems ◽  
Galerkin Projection ◽  
Line Contact ◽  
Reduced Order ◽  
Fast Solution ◽  
Speed Up ◽  
Newton Raphson ◽  
First Time ◽  
Piecewise Linear Approach

In order to obtain a fast solution scheme, the trajectory piecewise linear (TPWL) method is applied to the transient elastohydrodynamic (EHD) line contact problem for the first time. TPWL approximates the nonlinearity of a dynamical system by a weighted superposition of reduced linearized systems along specified trajectories. The method is compared to another reduced order model (ROM), based on Galerkin projection, Newton–Raphson scheme and an approximation of the nonlinear reduced system functions. The TPWL model provides further speed-up compared to the Newton–Raphson based method at a high accuracy.

Improving Matsui’s Search Algorithm For The Best Differential/Linear Trails And Its Applications For DES, DESL And GIFT

2020 ◽  
Author(s):  
Fulei Ji ◽  
Wentao Zhang ◽  
Tianyou Ding
Keyword(s):  
Search Algorithm ◽  
Search Space ◽  
Search Methods ◽  
New Methods ◽  
Linear Layer ◽  
Speed Up ◽  
Automatic Search ◽  
The Cost ◽  
First Time ◽  
Improved Algorithm

Abstract Automatic search methods have been widely used for cryptanalysis of block ciphers, especially for the most classic cryptanalysis methods—differential and linear cryptanalysis. However, the automatic search methods, no matter based on MILP, SMT/SAT or CP techniques, can be inefficient when the search space is too large. In this paper, we propose three new methods to improve Matsui’s branch-and-bound search algorithm, which is known as the first generic algorithm for finding the best differential and linear trails. The three methods, named reconstructing DDT and LAT according to weight, executing linear layer operations in minimal cost and merging two 4-bit S-boxes into one 8-bit S-box, respectively, can efficiently speed up the search process by reducing the search space as much as possible and reducing the cost of executing linear layer operations. We apply our improved algorithm to DESL and GIFT, which are still the hard instances for the automatic search methods. As a result, we find the best differential trails for DESL (up to 14-round) and GIFT-128 (up to 19-round). The best linear trails for DESL (up to 16-round), GIFT-128 (up to 10-round) and GIFT-64 (up to 15-round) are also found. To the best of our knowledge, these security bounds for DESL and GIFT under single-key scenario are given for the first time. Meanwhile, it is the longest exploitable (differential or linear) trails for DESL and GIFT. Furthermore, benefiting from the efficiency of the improved algorithm, we do experiments to demonstrate that the clustering effect of differential trails for 13-round DES and DESL are both weak.

Dialectisms in the novella “The Ravine” by S.A. Yesenin

Neophilology ◽  
2019 ◽  
pp. 282-292
Author(s):  
Elena V. LOGACHEVA
Keyword(s):  
Morphological Diversity ◽  
Component Analysis ◽  
Point Of View ◽  
Speech Activity ◽  
Part Of Speech ◽  
First Time ◽  
Individual Style

We analyze lexical and semantic originality and part of speech activity of dialect words as one of the stylistic dominants of the S.А. Yesenin’s novella “The Ravine” and as part of his in-dividual creative manner. This study was conducted for the first time. We consider the material using the methods of interpretation, component analysis, as well as structural descriptive and con-textual methods. In the course of working with the existing literature on this issue, we discover the lack of material coverage and the absence of dialect vocabulary analysis in the novella “The Ravine” from morphological point of view. We find the thematic, morphological diversity and reveal the manifestation specificity of local words in the author’s and dialogical speech of the work, as well as the functional validity of their application. We prove that the use of local words in novella is caused not only by the idea of novella being a village theme work, but also has a deep cognitive basis. The relevance of the study lies in the fact that conducted research of novella’s dialectal vo-cabulary allows to complement the knowledge of the specificity of S.A. Yesenin poetics’, his lin-guistic worldview and the peculiarity of his individual style.

scholarly journals Spatial dependence of the nonlinear BOLD response at short stimulus duration

NeuroImage ◽  
2003 ◽  
Vol 18 (4) ◽  
pp. 990-1000 ◽  
Author(s):  
Josef Pfeuffer ◽  
Jeffrey C McCullough ◽  
Pierre-Francois Van de Moortele ◽  
Kamil Ugurbil ◽  
Xiaoping Hu
Keyword(s):  
Stimulus Duration ◽  
Spatial Dependence ◽  
Bold Response ◽  
Short Stimulus ◽  
Short Stimulus Duration

scholarly journals Dartagnan: Leveraging Compiler Optimizations and the Price of Precision (Competition Contribution)

2021 ◽  
pp. 428-432
Author(s):  
Hernán Ponce-de-León ◽  
Thomas Haas ◽  
Roland Meyer
Keyword(s):  
Model Checking ◽  
Bounded Model Checking ◽  
Model Checker ◽  
Compiler Optimizations ◽  
Sequential Programs ◽  
Input Program ◽  
Order Of Magnitude ◽  
Speed Up ◽  
First Time ◽  
Bitwise Operations

AbstractWe describe the new features of the bounded model checker Dartagnan for SV-COMP ’21. We participate, for the first time, in the ReachSafety category on the verification of sequential programs. In some of these verification tasks, bugs only show up after many loop iterations, which is a challenge for bounded model checking. We address the challenge by simplifying the structure of the input program while preserving its semantics. For simplification, we leverage common compiler optimizations, which we get for free by using LLVM. Yet, there is a price to pay. Compiler optimizations may introduce bitwise operations, which require bit-precise reasoning. We evaluated an SMT encoding based on the theory of integers + bit conversions against one based on the theory of bit-vectors and found that the latter yields better performance. Compared to the unoptimized version of Dartagnan, the combination of compiler optimizations and bit-vectors yields a speed-up of an order of magnitude on average.

scholarly journals Deep COVID 19: Deep Learning for COVID 19 Detection from X ray Images

2021 ◽  
Vol 11 (1) ◽  
pp. 1-6
Author(s):  
Ahmed Hashem El Fiky ◽  
Keyword(s):  
Machine Learning Algorithms ◽  
Diagnostic Process ◽  
X Rays ◽  
Virus Spread ◽  
Large Dataset ◽  
X Ray ◽  
Support Mechanism ◽  
Proposed Model ◽  
Speed Up ◽  
First Time

The COVID-19 will take place for the first time in December 2019 in Wuhan, China. After that, the virus spread all over the world, with over 4.7 million confirmed cases and over 315000 deaths as of the time of writing this report. Radiologists can employ machine learning algorithms developed on radiography pictures as a decision support mechanism to help them speed up the diagnostic process. The goal of this study is to conduct a quantitative evaluation of six off-the-shelf convolutional neural networks (CNNs) for COVID-19 X-ray image analysis. Due to the limited amount of images available for analysis, the CNN transfer learning approach was used. We also developed a simple CNN architecture with a modest number of parameters that does a good job of differentiating COVID-19 from regular X-rays. in this paper, we are used large dataset which contained CXR images of normal patients and patients with COVID-19. the number of CXR images for normal patients are 10,192 image and the number of CXR images for COVID-19 patients are 3,616 images. The results of experiments show the effectiveness and robustness of Deep-COVID-19 and pretrained models like VGG16, VGG19, and MobileNets. Our proposed Model Deep-COVID-19 achieved over 94.5% accuracy.

scholarly journals Uncovering the Concentration Phenomenon of Vehicle Mobility in Urban Areas

2019 ◽  
Author(s):  
BING ZOU
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Wealth Distribution ◽  
Interesting Phenomenon ◽  
The Road ◽  
Urban City ◽  
Division Point ◽  
Vehicle Mobility ◽  
Transportation Research ◽  
First Time

Extracting the regularity of individual vehicle mobility has long been a general research topic that has numerous applications for urban management and services. In this paper, we combine vehicle mobility information extracted from vehicle identification data with a large and directed road network, to understand vehicle mobility and how it shapes the road usage profile in an urban city. We propose here a versatile method to extract the division point of vehicle mobility distribution, which is designed to observe the interesting phenomenon whereby, similar to the inequality in wealth distribution in economics, surprisingly few vehicles contribute to the larger proportion of road usage. Based on the relationship between vehicle mobility and urban roads, we reveal road usage profile (e.g. central, transit, branch, local), depending on traffic flow and vehicle mobility inequality features, in contrast to traditional topology indicators and aggregated indicators.We also validate for the first time a methodology which uncovers the road usage characteristics from the microscopic perspective of vehicles. These results allow us to create a quantitative strategy to note the few but decisive vehicles that add to traffic congestion and to put into perspective the transition from traditional aggregated approaches to individual-based practices in transportation research.

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