scholarly journals Hypnotic Metaphor аs a Discursive Mechanism of Speech Influence (a Case Study of Psychological Trainings by Natalia Grace)

2020 ◽  
pp. 50-58
Author(s):  
Elena A. Kozlova ◽  
Keyword(s):  
Mirror Neurons ◽  
Right Hemisphere ◽  
Object Code ◽  
Metaphorical Thinking ◽  
Psychotherapy Session ◽  
Basic Layer ◽  
The Right ◽  
And Linguistics

The article deals with the concept of hypnotic metaphor in psychiatry and linguistics and explores its application in the situation of public teaching discourse. The right-hemisphere mechanisms of perception are considered in order to detect sensory images, represented in the universal object code, since the processes of mastering the facts, which are based on similarity, adjacency, imagery, take place in the right hemisphere. The connection of mirror neurons with metaphorical thinking is assumed. The classification of metaphor types in psychotherapeutic literature is given. The article analyzes the performance of modern speaker-coaches, given as lectures, trainings, conversations and designed to effectively change the emotional mood and categorical constructs of listeners. Otherwise, listeners simply will not buy tickets for these events. It is concluded that modern lecture trainings are a kind of group psychotherapy session. Information is fed in a ‘live stream’ of right-hemisphere mechanisms involving mirror neurons. Coach rhetoric is a system of metaphors that are archetypes of consciousness and are part of the basic layer of the conceptual framework.

scholarly journals DECISION TREE C4.5 ALGORITHM FOR TUITION AID GRANT PROGRAM CLASSIFICATION (CASE STUDY: DEPARTMENT OF INFORMATION SYSTEM, UNIVERSITAS TEKNOKRAT INDONESIA)

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Heni Sulistiani ◽  
Ahmad Ari Aldino
Keyword(s):  
Decision Tree ◽  
Classification Model ◽  
Grant Program ◽  
C4.5 Algorithm ◽  
Long Time ◽  
The Right ◽  
Short Time ◽  
Tuition Fee

In pandemic era, almost everyone struggles for their life. College students are such example. They have difficulty in paying tuition fee to continue their study. Based on this problematic situation, Universitas Teknokrat Indonesia grants the students who have good academic performance with tuition fee aid program. Many variables used for determining the grant made it hard to make a decision in a short time or even takes very long time. To make it easier for management to decide who is the right student to get grant, it needs classification model. The purpose of this study is the classification of grant recipients by using decision tree C4.5 algorithm. That can determine whether a potential student can be accepted as an awardee or not. Then, the results of the classification are validated with ten-fold cross validation with an accuracy, precision and recall with the score of 87 % for all part. It means the model perform quite well to be implemented into system.

Using Fractal and Local Binary Pattern Features for Classification of ECOG Motor Imagery Tasks Obtained from the Right Brain Hemisphere

2016 ◽  
Vol 26 (06) ◽  
pp. 1650022 ◽  
Author(s):  
Fangzhou Xu ◽  
Weidong Zhou ◽  
Yilin Zhen ◽  
Qi Yuan ◽  
Qi Wu
Keyword(s):  
Motor Imagery ◽  
Local Binary Pattern ◽  
Right Hemisphere ◽  
Ordinary Least Squares ◽  
Superior Performance ◽  
Gradient Boosting ◽  
The Right ◽  
The Brain ◽  
Combined Feature

The feature extraction and classification of brain signal is very significant in brain–computer interface (BCI). In this study, we describe an algorithm for motor imagery (MI) classification of electrocorticogram (ECoG)-based BCI. The proposed approach employs multi-resolution fractal measures and local binary pattern (LBP) operators to form a combined feature for characterizing an ECoG epoch recording from the right hemisphere of the brain. A classifier is trained by using the gradient boosting in conjunction with ordinary least squares (OLS) method. The fractal intercept, lacunarity and LBP features are extracted to classify imagined movements of either the left small finger or the tongue. Experimental results on dataset I of BCI competition III demonstrate the superior performance of our method. The cross-validation accuracy and accuracy is 90.6% and 95%, respectively. Furthermore, the low computational burden of this method makes it a promising candidate for real-time BCI systems.

Emotions Are Rising: The Growing Field of Affect Neuropsychology

2017 ◽  
Vol 23 (9-10) ◽  
pp. 719-731 ◽  
Author(s):  
Skye McDonald
Keyword(s):  
Cognitive Processing ◽  
Mirror Neurons ◽  
Right Hemisphere ◽  
Task Demands ◽  
Careful Examination ◽  
Somatic Marker ◽  
Cortical Responses ◽  
Mri Scans ◽  
Magnetic Resonance Imaging Mri ◽  
The Right

AbstractThirty years ago, the neuropsychology of emotion started to emerge as a mainstream topic. Careful examination of individual patients showed that emotion, like memory, language, and so on, could be differentially affected by brain disorders, especially in the right hemisphere. Since then, there has been accelerating interest in uncovering the neural architecture of emotion, and the major steps in this process of discovery over the past 3 decades are detailed in this review. In the 1990s, magnetic resonance imaging (MRI) scans provided precise delineation of lesions in the amygdala, medial prefrontal cortex, insula and somatosensory cortex as underpinning emotion disorders. At the same time, functional MRI revealed activation that was bilateral and also lateralized according to task demands. In the 2000s, converging evidence suggested at least two routes to emotional responses: subcortical, automatic and autonomic responses and slower, cortical responses mediating cognitive processing. The discovery of mirror neurons in the 1990s reinvigorated older views that simulation was the means to recognize emotions and empathize with others. More recently, psychophysiological research, revisiting older Russian paradigms, has contributed new insights into how autonomic and other physiological indices contribute to decision making (the somatic marker theory), emotional simulation, and social cognition. Finally, this review considers the extent to which these seismic changes in understanding emotional processes in clinical disorders have been reflected in neuropsychological practice. (JINS, 2017, 23, 719–731)

Pure alexia without agraphia after a lesion at the right hemisphere: A case study

2005 ◽  
Vol 95 (1) ◽  
pp. 239-240 ◽  
Author(s):  
K. Tsapkini ◽  
O. Dimos ◽  
Z. Katsarou
Keyword(s):  
Right Hemisphere ◽  
Pure Alexia ◽  
The Right

scholarly journals Hemispheric antagonism in visuo-spatial neglect: A case study

1996 ◽  
Vol 2 (5) ◽  
pp. 412-418 ◽  
Author(s):  
John C. Marshall ◽  
Peter W. Halligan
Keyword(s):  
Right Hemisphere ◽  
Task Demands ◽  
Line Bisection ◽  
Spatial Neglect ◽  
Perceptual Task ◽  
Left Hand ◽  
Right Hand ◽  
The Right ◽  
Line Bisection Task

AbstractWe report a case of severe visuo-spatial neglect consequent upon right-hemisphere stroke. At the time of testing, the patient had no visual field cut and no significant hemiparesis. Conventional testing on cancellation tasks with the right hand revealed reliable left neglect, but performance was significantly improved when the left hand was used. Investigations of (manual) line bisection showed normal performance with the right hand but right neglect when the left hand was used. Right neglect was also observed on a purely perceptual version of the line bisection task. We argue that the attentional vectors of the cerebral hemispheres can be modulated by (perceptual) task-demands and by (motorie) response demands. (JINS, 1996, 2, 412–418.)

Investigating the phonemic categorization capacity of the right hemisphere: A case study

2007 ◽  
Vol 103 (1-2) ◽  
pp. 160-161
Author(s):  
M. Wolmetz ◽  
B. Rapp ◽  
D. Poeppel
Keyword(s):  
Right Hemisphere ◽  
The Right

Recognition of Natural Expressions of Emotion by CVA Patients with Damage to the Left or Right Hemisphere

2002 ◽  
Vol 3 (1) ◽  
pp. 42-53
Author(s):  
Rebecca Bowen ◽  
Skye McDonald
Keyword(s):  
Cerebrovascular Accident ◽  
Cerebral Hemisphere ◽  
Visual Cues ◽  
Right Hemisphere ◽  
Negative Emotions ◽  
Statistical Analyses ◽  
Left Cerebral Hemisphere ◽  
Complex Stimuli ◽  
The Right

AbstractThe present study investigated the ability of cerebrovascular accident (CVA) patients to perceive emotions portrayed by realistic stimuli. Statistical analyses demonstrated that CVA patients with damage to either the right or left cerebral hemisphere performed, on average, as well as controls did in perceiving emotions. However, a case study of one patient suggested that there may be a subset of CVA patients with right parieto-occipital damage who have deficits in the perception of negative emotions. The performance of this participant also indicated that deficits in emotion perception are ameliorated to some extent when patients are provided with realistic, complex stimuli that include a range of auditory and visual cues.

scholarly journals Analysis and classification of companies on Tehran Stock Exchange with Incomplete Information

2020 ◽  
Author(s):  
Alireza Komeili Birjandi ◽  
Sanaz Dehmolaee ◽  
Reza Sheikh ◽  
Shib Sankar Sana
Keyword(s):  
Incomplete Information ◽  
Financial Market ◽  
Capital Market ◽  
Stock Exchange ◽  
Preference Relation ◽  
Main Concern ◽  
Preferred Stock ◽  
The Right

Due to uncertainty and large number of companies in financial market, it has become difficult to choose the right stock to investments. Identifying and classifying stocks using fundamental criteria help investors to better understand the risks involved in selecting companies and better manage their own capital, thereby rapidly and accurately choose their preferred stock and make more secure profit. The main concern that capital market investors are facing difficulty to choosing the right stock despite the uncertainties in the market. Uncertainties in the market that lead to incomplete information are presented in this article to complete the reciprocal preference relation method. The purpose of this paper is to present a method for completing information to reduce the uncertainties in the market and finally classify companies in each industry based on fundamental criteria. The classification method used is acceptability / reject ability which is based on distance fuzzy analysis yields more accurate results. Finally, a case study on one of the most critical industries in Tehran Stock Exchange is presented to show the effectiveness of the proposed approach.

Artificial neural networks for fly identification: A case study from the genera Tachina and Ectophasia (Diptera, Tachinidae)

Biologia ◽  
2007 ◽  
Vol 62 (4) ◽  
Author(s):  
Jaromír Vaňhara ◽  
Natália Muráriková ◽  
Igor Malenovský ◽  
Josef Havel
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Correct Identification ◽  
Training Set ◽  
Image Analyser ◽  
Artificial Neural ◽  
Reliable Classification ◽  
The Right

AbstractThe classification methodology based on morphometric data and supervised artificial neural networks (ANN) was tested on five fly species of the parasitoid genera Tachina and Ectophasia (Diptera, Tachinidae). Objects were initially photographed, then digitalized; consequently the picture was scaled and measured by means of an image analyser. The 16 variables used for classification included length of different wing veins or their parts and width of antennal segments. The sex was found to have some influence on the data and was included in the study as another input variable. Better and reliable classification was obtained when data from both the right and left wings were entered, the data from one wing were however found to be sufficient. The prediction success (correct identification of unknown test samples) varied from 88 to 100% throughout the study depending especially on the number of specimens in the training set. Classification of the studied Diptera species using ANN is possible assuming a sufficiently high number (tens) of specimens of each species is available for the ANN training. The methodology proposed is quite general and can be applied for all biological objects where it is possible to define adequate diagnostic characters and create the appropriate database.

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