Dynamic features of auditory bistable perception extracted from human electrocorticography recordings

2021 ◽  
Author(s):  
Pake Melland
Keyword(s):  
Dynamic Features ◽  
Bistable Perception

A Dynamic View of Global Integration and Local Responsiveness Framework

2018 ◽  
Vol 6 (8) ◽  
pp. 58
Author(s):  
Uyen-Minh Le ◽  
Tung-Shan Liao
Keyword(s):  
International Business ◽  
Business Management ◽  
External Environment ◽  
Dynamic Capability ◽  
International Strategy ◽  
Global Integration ◽  
Dynamic Features ◽  
Dynamic View ◽  
Concept Building ◽  
Strategy Types

Global-Integration and Local-Responsiveness (IR) framework with four pairs of external environment and appropriate international strategy types has contributed significantly to international business management. Nevertheless, the framework is still incomplete and lacks dynamic features. To deal with such limitations and enhance the theory, this paper, therefore, brings dynamic features regarding both environment and strategy into the IR grid. Under a dynamic capability angle with three steps of sensing, seizing and transforming [30], the dynamic global integration and local responsiveness framework – a new concept building for international business – would be explicated.

STRUCTURAL AND DYNAMIC FEATURES OF EAR-LY DISABILITY DUE TO MENTAL DISEASES

2020 ◽  
pp. 62-67
Author(s):  
Shmakova O.P.
Keyword(s):  
People With Disabilities ◽  
Child And Adolescent Psychiatry ◽  
Child Psychiatrist ◽  
Childhood And Adolescence ◽  
Disabled Children ◽  
Dynamic Features ◽  
Factors Affecting ◽  
Number Of Children ◽  
Number Of Patients

Prevention of disability is one of the most significant tasks of child and adolescent psychiatry. Obtaining data on the dynamics of the number of people with disabilities and the factors affecting this indicator seems to be one of the relevant aspects. Aim: to trace the dynamics of the number of children with disabili-ties and to assess the change in the structure of early disability over the past decades. Materials and Meth-ods. A comparative analysis of two cohorts of patients was carried out: 1st - patients born in 1990-1992. (1203 patients (men - 914, 76%; women - 289, 24%)) who applied to the district neuropsychiatric dispensa-ry for outpatient care in childhood and adolescence; II - children and adolescents born in 2005 - 2018 (602 patients (male - 410, 68%; female - 192, 32%), ob-served at the time of the study by a child psychiatrist in the neuropsychiatric dispensary. Research methods: clinical and psychopathological; follow-up; statisti-cal. Results. Comparison of the number and nosologi-cal distribution of disabled children in two cohorts showed that over the 15th year there has been a shift towards an increase in the proportion of disabled children among patients observed by child and ado-lescent psychiatrists. The increase in the number of children with disabilities was due to those suffering from childhood autism and other disorders of general development. There were no statistically significant differences in the number of people with disabilities who received benefits before the age of 7, as well as differences in gender ratios among disabled people in the two cohorts. Conclusion. Early disability is a mul-tifactorial phenomenon, prevalence, dynamics, the structure of which depends not only on clinical, but also on socio-administrative realities. Children with autism require increased attention, since there has been a multiple increase in the number of patients with this diagnosis.

DEVELOPMENT OF THE BASIC CRITERIA FOR RUSSIAN COASTS TYPIFICATION

2017 ◽  
Author(s):  
Рубен Косян ◽  
Ruben Kosyan ◽  
Viacheslav Krylenko ◽  
Viacheslav Krylenko
Keyword(s):  
Coastal Zone ◽  
Coastal Area ◽  
Economic Activity ◽  
Basic Information ◽  
Dynamic Features ◽  
Static State ◽  
Evolutionary Features ◽  
Coastal Features ◽  
The Stability

There are many types of coasts classifications that indicate main coastal features. As a rule, the "static" state of the coasts is considered regardless of their evolutionary features and ways to further transformation. Since the most part of the coastal zone studies aimed at ensuring of economic activity, it is clear that the classification of coast types should indicate total information required by the users. Accordingly, the coast classification should include the criterion, characterizing as dynamic features of the coast and the conditions and opportunities of economic activity. The coast classification, of course, should be based on geomorphological coast typification. Similar typification has been developed by leading scientists from Russia and can be used with minimal modifications. The authors propose to add to basic information (geomorphological type of coast) the evaluative part for each coast sector. It will include the estimation of the coast changes probability and the complexity of the coast stabilization for economic activity. This method will allow to assess the dynamics of specific coastal sections and the processes intensity and, as a result – the stability of the coastal area.

scholarly journals Radiomic and Artificial Intelligence Analysis with Textural Metrics, Morphological and Dynamic Perfusion Features Extracted by Dynamic Contrast-Enhanced Magnetic Resonance Imaging in the Classification of Breast Lesions

2021 ◽  
Vol 11 (4) ◽  
pp. 1880
Author(s):  
Roberta Fusco ◽  
Adele Piccirillo ◽  
Mario Sansone ◽  
Vincenza Granata ◽  
Paolo Vallone ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Artificial Intelligence ◽  
Feature Selection ◽  
Resonance Imaging ◽  
Dynamic Features ◽  
Surgical Specimen ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced ◽  
Malignant Lesions

Purpose: The aim of the study was to estimate the diagnostic accuracy of textural, morphological and dynamic features, extracted by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) images, by carrying out univariate and multivariate statistical analyses including artificial intelligence approaches. Methods: In total, 85 patients with known breast lesion were enrolled in this retrospective study according to regulations issued by the local Institutional Review Board. All patients underwent DCE-MRI examination. The reference standard was pathology from a surgical specimen for malignant lesions and pathology from a surgical specimen or fine needle aspiration cytology, core or Tru-Cut needle biopsy for benign lesions. In total, 91 samples of 85 patients were analyzed. Furthermore, 48 textural metrics, 15 morphological and 81 dynamic parameters were extracted by manually segmenting regions of interest. Statistical analyses including univariate and multivariate approaches were performed: non-parametric Wilcoxon–Mann–Whitney test; receiver operating characteristic (ROC), linear classifier (LDA), decision tree (DT), k-nearest neighbors (KNN), and support vector machine (SVM) were utilized. A balancing approach and feature selection methods were used. Results: The univariate analysis showed low accuracy and area under the curve (AUC) for all considered features. Instead, in the multivariate textural analysis, the best performance (accuracy (ACC) = 0.78; AUC = 0.78) was reached with all 48 metrics and an LDA trained with balanced data. The best performance (ACC = 0.75; AUC = 0.80) using morphological features was reached with an SVM trained with 10-fold cross-variation (CV) and balanced data (with adaptive synthetic (ADASYN) function) and a subset of five robust morphological features (circularity, rectangularity, sphericity, gleaning and surface). The best performance (ACC = 0.82; AUC = 0.83) using dynamic features was reached with a trained SVM and balanced data (with ADASYN function). Conclusion: Multivariate analyses using pattern recognition approaches, including all morphological, textural and dynamic features, optimized by adaptive synthetic sampling and feature selection operations obtained the best results and showed the best performance in the discrimination of benign and malignant lesions.

scholarly journals A Comparative Analysis on Probability of Volatility Clusters on Cryptocurrencies, and FOREX Currencies

2021 ◽  
Vol 14 (7) ◽  
pp. 308
Author(s):  
Usha Rekha Chinthapalli
Keyword(s):  
Investment Decision ◽  
Theoretical Work ◽  
Financial Asset ◽  
Dynamic Features ◽  
Asset Return ◽  
Financial Variables ◽  
Ann Models ◽  
Hidden Layer ◽  
Association Structure ◽  
The Impact

In recent years, the attention of investors, practitioners and academics has grown in cryptocurrency. Initially, the cryptocurrency was designed as a viable digital currency implementation, and subsequently, numerous derivatives were produced in a range of sectors, including nonmonetary activities, financial transactions, and even capital management. The high volatility of exchange rates is one of the main features of cryptocurrencies. The article presents an interesting way to estimate the probability of cryptocurrency volatility clusters. In this regard, the paper explores exponential hybrid methodologies GARCH (or EGARCH) and through its portrayal as a financial asset, ANN models will provide analytical insight into bitcoin. Meanwhile, more scalable modelling is needed to fit financial variable characteristics such as ANN models because of the dynamic, nonlinear association structure between financial variables. For financial forecasting, BP is contained in the most popular methods of neural network training. The backpropagation method is employed to train the two models to determine which one performs the best in terms of predicting. This architecture consists of one hidden layer and one input layer with N neurons. Recent theoretical work on crypto-asset return behavior and risk management is supported by this research. In comparison with other traditional asset classes, these results give appropriate data on the behavior, allowing them to adopt the suitable investment decision. The study conclusions are based on a comparison between the dynamic features of cryptocurrencies and FOREX Currency’s traditional mass financial asset. Thus, the result illustrates how well the probability clusters show the impact on cryptocurrency and currencies. This research covers the sample period between August 2017 and August 2020, as cryptocurrency became popular around that period. The following methodology was implemented and simulated using Eviews and SPSS software. The performance evaluation of the cryptocurrencies is compared with FOREX currencies for better comparative study respectively.

Application of Digital Simulation Software ANSYS in Rolling Concrete Dams Construction Technology

2011 ◽  
Vol 704-705 ◽  
pp. 352-357
Author(s):  
Gui Xiang Zeng
Keyword(s):  
Digital Simulation ◽  
Simulation Software ◽  
Construction Technology ◽  
Dynamic Features ◽  
Concrete Gravity Dam ◽  
Gravity Dams ◽  
Concrete Dam ◽  
Concrete Gravity Dams ◽  
Xinjiang Autonomous Region ◽  
Important Significance

Taking a large hydropower station in Xinjiang Autonomous Region as an example, and based on the limited unit method, the structure and seism forces features and response rules of rolling concrete gravity dam under different construction conditions were studied. The purpose for the paper is to understand dam working status under the different design conditions, and to evaluate anti-earthquake safety capability. It is proved that the present findings should play an important significance in the development of rolling concrete dam construction technology. Key words: Rolling Concrete Gravity Dams, Limited Unit Methods, Static Force Analysis, Dynamic Features.

Predictors of professional commitment for Chinese new generation cohorts in a sample of seafaring officers

2021 ◽  
pp. 1-17
Author(s):  
Xiaohui Jia
Keyword(s):  
Regression Analysis ◽  
Questionnaire Survey ◽  
Important Predictor ◽  
Professional Commitment ◽  
Hierarchical Regression ◽  
Dynamic Features ◽  
Hierarchical Regression Analysis ◽  
Generation Cohorts ◽  
New Generation

Abstract This study aims to examine the predictors of professional commitment of the Chinese new generation, divided into post-80s and post-90s cohorts. A questionnaire survey was employed to collect data from Chinese seafaring officers of these cohorts. The results through hierarchical regression analysis present the two cohorts as having both similar and different predictors. The main difference is that company management and policies positively drive the post-80s cohort to work at sea but not the post-90s. The main similarity is that the work itself is the most important predictor for both cohorts. This study contributes to helping maritime companies to estimate the possibility of Chinese new generation officers quitting sea jobs and can be of value to both managers and authorities as they seek to comprehend the generational dynamic features to better cope with the problem of shortage of younger qualified officers.

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