scholarly journals A hybrid analytical–numerical algorithm for determining the neuronal current via electroencephalography

2020 ◽  
Vol 17 (163) ◽  
pp. 20190831 ◽  
Author(s):  
Parham Hashemzadeh ◽  
A. S. Fokas ◽  
C. B. Schönlieb
Keyword(s):  
Electric Potential ◽  
Focal Epilepsy ◽  
Synthetic Data ◽  
Real Data ◽  
Auxiliary Function ◽  
Alternative Approach ◽  
Eeg Data ◽  
Neuronal Current ◽  
The Given

Specific mental processes are associated with brain activation of a unique form, which are, in turn, expressed via the generation of specific neuronal electric currents. Electroencephalography (EEG) is based on measurements on the scalp of the electric potential generated by the neuronal current flowing in the cortex. This specific form of EEG data has been employed for a plethora of medical applications, from sleep studies to diagnosing focal epilepsy. In recent years, there have been efforts to use EEG data for a more ambitious purpose, namely to determine the underlying neuronal current. Although it has been known since 1853, from the studies by Helmholtz, that the knowledge of the electric potential of the external surface of a conductor is insufficient for the determination of the electric current that gave rise to this potential, the important question of which part of the current can actually be determined from the knowledge of this potential remained open until work published in 1997, when it was shown that EEG provides information only about the irrotational part of the current, which will be denoted by Ψ ; moreover, an explicit formula was derived in the above work relating this part of the current, the measured electric potential, and a certain auxiliary function, v s , that depends on the geometry of the various compartments of the brain–head system and their conductivities. In the present paper: (i) Motivated by recent results which show that, in the case of ellipsoidal geometry, the assumption of the L 2 minimization of the current yields a unique solution, we derive an analogous analytic formula characterizing this minimization for arbitrary geometry. (ii) We show that the above auxiliary function can be computed numerically via a line integral from the values of a related function v s computed via OpenMEEG; moreover, we propose an alternative approach to computing the auxiliary function v s based on the construction of a certain surrogate model. (iii) By expanding Ψ in terms of an inverse multiquadric radial basis we implement the relevant formulae numerically. The above algorithm performs well for synthetic data; its implementation with real data only requires the knowledge of the coordinates of the positions where the given EEG data are obtained.

Method of determination of the text direction on the image with the use of convolutional neural network

2020 ◽  
pp. 96-99
Author(s):  
P.L. Nikolaev
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Deep Neural Network ◽  
Binary Classification ◽  
Synthetic Data ◽  
Real Data ◽  
Method Of Determination ◽  
Classification Of Images

This article deals with method of binary classification of images with small text on them Classification is based on the fact that the text can have 2 directions – it can be positioned horizontally and read from left to right or it can be turned 180 degrees so the image must be rotated to read the sign. This type of text can be found on the covers of a variety of books, so in case of recognizing the covers, it is necessary first to determine the direction of the text before we will directly recognize it. The article suggests the development of a deep neural network for determination of the text position in the context of book covers recognizing. The results of training and testing of a convolutional neural network on synthetic data as well as the examples of the network functioning on the real data are presented.

LEARNING GENE NETWORK USING TIME-DELAYED BAYESIAN NETWORK

2006 ◽  
Vol 15 (03) ◽  
pp. 353-370 ◽  
Author(s):  
TIE-FEI LIU ◽  
WING-KIN SUNG ◽  
ANKUSH MITTAL
Keyword(s):  
Time Delay ◽  
Gene Networks ◽  
Gene Network ◽  
Structure Learning ◽  
Learning Algorithm ◽  
Research Work ◽  
Synthetic Data ◽  
Real Data ◽  
Information Criterion

Exact determination of a gene network is required to discover the higher-order structures of an organism and to interpret its behavior. Most research work in learning gene networks either assumes that there is no time delay in gene expression or that there is a constant time delay. This paper shows how Bayesian Networks can be applied to represent multi-time delay relationships as well as directed loops. The intractability of the network learning algorithm is handled by using an improved mutual information criterion. Also, a new structure learning algorithm, "Learning By Modification", is proposed to learn the sparse structure of a gene network. The experimental results on synthetic data and real data show that our method is more accurate in determining the gene structure as compared to the traditional methods. Even transcriptional loops spanning over the whole cell can be detected by our algorithm.

scholarly journals Determination of quasi-primary odors by endpoint detection

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hanxiao Xu ◽  
Koki Kitai ◽  
Kosuke Minami ◽  
Makito Nakatsu ◽  
Genki Yoshikawa ◽  
...  
Keyword(s):  
Machine Learning ◽  
Arbitrary Number ◽  
The Other ◽  
Endpoint Detection ◽  
Alternative Approach ◽  
The Given

AbstractIt is known that there are no primary odors that can represent any other odors with their combination. Here, we propose an alternative approach: “quasi” primary odors. This approach comprises the following condition and method: (1) within a collected dataset and (2) by the machine learning-based endpoint detection. The quasi-primary odors are selected from the odors included in a collected odor dataset according to the endpoint score. While it is limited within the given dataset, the combination of such quasi-primary odors with certain ratios can reproduce any other odor in the dataset. To visually demonstrate this approach, the three quasi-primary odors having top three high endpoint scores are assigned to the vertices of a chromaticity triangle with red, green, and blue. Then, the other odors in the dataset are projected onto the chromaticity triangle to have their unique colors. The number of quasi-primary odors is not limited to three but can be set to an arbitrary number. With this approach, one can first find “extreme” odors (i.e., quasi-primary odors) in a given odor dataset, and then, reproduce any other odor in the dataset or even synthesize a new arbitrary odor by combining such quasi-primary odors with certain ratios.

The Role and Place of Budget Procedure in the System

2003 ◽  
pp. 42-49 ◽  
Author(s):  
E. Bushmin
Keyword(s):  
Budget Process ◽  
Public Expenditures ◽  
Principal Role ◽  
Process Trends ◽  
The Given ◽  
Rules Of The Game

The article is devoted to the analysis of improving budget process trends. The author offers the concept of "financial technologism". Its usage should promote an essential improvement of the budget process. The given concept is based on the fact that the regulation of budget procedure is the process of determination of "rules of the game", and the order of interaction of different institutions within the framework of the budget process, and the trends and volumes of expenses are the strategy of institutions. The procedure within the budget process plays a principal role as compared with the trends and volumes of public expenditures.

MODIFIKASI MODEL PEMBELAJARAN TEAM ASSISTED INDIVIDUALIZATION DENGAN STRATEGI PEMBELAJARAN TUGAS DAN PAKSA

2019 ◽  
Vol 2 ◽  
Author(s):  
Lea Christy Restu Kinasih ◽  
Dewi Fatimah ◽  
Veranica Julianti
Keyword(s):  
Cooperative Learning ◽  
Learning Strategies ◽  
Learning Process ◽  
Learning Model ◽  
Learning Models ◽  
Classroom Learning ◽  
Quality Of Learning ◽  
The Given

The selection and determination of appropriate learning strategies can improve the results to be obtained from the application of classroom learning models. This writing aims to discipline students to develop individual abilities of students to be more active in the learning process and improve the quality of learning. The learning process in Indonesia in general only uses conventional learning models that make students passive and undeveloped. In order for the quality of learning to increase, the Team Assisted Individualization learning model is combined with the task learning and forced strategies. The Team Assisted Individualization cooperative learning model is one of the cooperative learning models that combines learning individually and in groups. Meanwhile, task and forced learning strategies are strategies that focus on giving assignments that require students to complete them on time so that the learning process can run effectively. Students are required to do assignments according to the given deadline. This makes students become familiar with the tasks given by the teacher. Combining or modifying the learning model of the assisted individualization team with forced and forced learning strategies is expected to be able to make students more active, disciplined, independent, creative in learning and responsible for the tasks assigned. Therefore this method of incorporation is very necessary in the learning process and can be applied to improve the quality of learning in schools.

MANUFACTURE INVESTIGATION OF CARTRIDGE WITH BOTTOM-MOST PART FLANGE BY DIRECT EXTRUSION WITH COUNTERPUNCH. REPORT 13. DETERMINATION OF DEFORMED STATE UNDER STRAITENED EXTRUSION IN FOURTH CENTRAL AREA OF PLASTIC DEFORMATION

2020 ◽  
Vol 0 (4) ◽  
pp. 43-51
Author(s):  
A. L. Vorontsov ◽  
◽  
I. A. Nikiforov ◽  
Keyword(s):  
Plastic Deformation ◽  
Plastic Flow ◽  
Central Area ◽  
Direct Extrusion ◽  
Deformed State ◽  
Cumulative Deformation ◽  
The Given ◽  
General Method

Formulae have been obtained that are necessary to calculate cumulative deformation in the process of straitened extrusion in the central area closed to the working end of the counterpunch. The general method of plastic flow proposed by A. L. Vorontsov was used. The obtained formulae allow one to determine the deformed state of a billet in any point of the given area. The formulae should be used to take into account the strengthening of the extruded material.

Influence of a chemical preparation of triazole50% cs on sowing the winter wheat against rust

2020 ◽  
Vol 3 (9) ◽  
pp. 231-233
Author(s):  
AliyevSh.K. ◽  
TuychiyevI.U ◽  
Karimov N ◽  
Umaraliev.M.I
Keyword(s):  
Winter Wheat ◽  
Field Experiments ◽  
Yellow Rust ◽  
Biological Efficiency ◽  
Chemical Preparation ◽  
Seed Growth ◽  
Biological Farming ◽  
The Given ◽  
Farming Efficiency

The article is focused on the data of the carried works on studying biological efficiency of fungi Triazole 50% on sowing the winter wheat against yellow rust as well as on the height, development and fertility of the wheat. On May 5, 2019 from 9 to 10 o’clock under the temperature 21-23 field experiments of Triazol 50% CS manufactured by the firm “Agroximstar” (Uzbekistan) were carried out on winter wheat as a protector of seeds of winter wheat of Pervitsa sort against the disease of yellow rustin the irrigated conditions in an experimental field of the Institute “Istiklal” of Andijan district of Andijan region. The aim of the given research is to study biological-farming efficiency and determination of optimal norms of preparation expenses and to study the influence of fungicide on the height and development as well as on the fertility of the wheat. The received data showed that the preparation Triazole 50% CS effected on the pathogen of yellow rust favorably and besides that it didn’t effect on seed growth and energy of growth negatively.

scholarly journals G-Tric: generating three-way synthetic datasets with triclustering solutions

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
João Lobo ◽  
Rui Henriques ◽  
Sara C. Madeira
Keyword(s):  
State Of The Art ◽  
Synthetic Data ◽  
Ground Truth ◽  
Real Data ◽  
Three Dimensions ◽  
Additional Advantage ◽  
Urban Dynamics ◽  
Data Generator ◽  
Real World Datasets ◽  
Synthetic Datasets

Abstract Background Three-way data started to gain popularity due to their increasing capacity to describe inherently multivariate and temporal events, such as biological responses, social interactions along time, urban dynamics, or complex geophysical phenomena. Triclustering, subspace clustering of three-way data, enables the discovery of patterns corresponding to data subspaces (triclusters) with values correlated across the three dimensions (observations $$\times$$ × features $$\times$$ × contexts). With increasing number of algorithms being proposed, effectively comparing them with state-of-the-art algorithms is paramount. These comparisons are usually performed using real data, without a known ground-truth, thus limiting the assessments. In this context, we propose a synthetic data generator, G-Tric, allowing the creation of synthetic datasets with configurable properties and the possibility to plant triclusters. The generator is prepared to create datasets resembling real 3-way data from biomedical and social data domains, with the additional advantage of further providing the ground truth (triclustering solution) as output. Results G-Tric can replicate real-world datasets and create new ones that match researchers needs across several properties, including data type (numeric or symbolic), dimensions, and background distribution. Users can tune the patterns and structure that characterize the planted triclusters (subspaces) and how they interact (overlapping). Data quality can also be controlled, by defining the amount of missing, noise or errors. Furthermore, a benchmark of datasets resembling real data is made available, together with the corresponding triclustering solutions (planted triclusters) and generating parameters. Conclusions Triclustering evaluation using G-Tric provides the possibility to combine both intrinsic and extrinsic metrics to compare solutions that produce more reliable analyses. A set of predefined datasets, mimicking widely used three-way data and exploring crucial properties was generated and made available, highlighting G-Tric’s potential to advance triclustering state-of-the-art by easing the process of evaluating the quality of new triclustering approaches.

Single Depth View Based Real-Time Reconstruction of Hand-Object Interactions

2021 ◽  
Vol 40 (3) ◽  
pp. 1-12
Author(s):  
Hao Zhang ◽  
Yuxiao Zhou ◽  
Yifei Tian ◽  
Jun-Hai Yong ◽  
Feng Xu
Keyword(s):  
Real Time ◽  
Synthetic Data ◽  
Real Data ◽  
Depth Image ◽  
Real Time System ◽  
The Real ◽  
Time Performance ◽  
Contact Constraint ◽  
Object Shapes ◽  
Object Interactions

Reconstructing hand-object interactions is a challenging task due to strong occlusions and complex motions. This article proposes a real-time system that uses a single depth stream to simultaneously reconstruct hand poses, object shape, and rigid/non-rigid motions. To achieve this, we first train a joint learning network to segment the hand and object in a depth image, and to predict the 3D keypoints of the hand. With most layers shared by the two tasks, computation cost is saved for the real-time performance. A hybrid dataset is constructed here to train the network with real data (to learn real-world distributions) and synthetic data (to cover variations of objects, motions, and viewpoints). Next, the depth of the two targets and the keypoints are used in a uniform optimization to reconstruct the interacting motions. Benefitting from a novel tangential contact constraint, the system not only solves the remaining ambiguities but also keeps the real-time performance. Experiments show that our system handles different hand and object shapes, various interactive motions, and moving cameras.

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