Visuo-Motor Adaptation to Stepwise and Gradual Changes in the Environment: Relationship between Consciousness and Adaptation

2001 ◽  
Vol 13 (6) ◽  
pp. 601-613 ◽  
Author(s):  
Yutaka Sakaguchi ◽  
◽  
Yu-ichi Akashi ◽  
Mitsuo Takano
Keyword(s):  
Numerical Experiments ◽  
External Environment ◽  
Motor Adaptation ◽  
Motor Command ◽  
Essential Factor ◽  
Modular Architecture ◽  
Visual Shift ◽  
Proposed Model ◽  
The Relationship ◽  
Psychological Experiments

Visuo-motor transformation in the human brain continuously adapts to the external environment, regardless of whether we are aware of the environmental change. This study examines the features of visuo-motor adaptation with stepwise and gradual visual shifts to explore the relationship between consciousness and adaptation. First, we ran psychological experiments, in which the amount of aftereffect was compared between the two kinds of visual shift. For most participants, almost complete aftereffects were observed in the gradual condition, while a slight aftereffect was observed in the stepwise condition. Interestingly, however, the magnitude of the aftereffect depended more on whether the participant noticed the visual shift than on whether the visual shift was stepwise or gradual. This suggests that participant consciousness is an essential factor in visuo-motor adaptation. Next, we built a computational model to simulate the experimental results. Its fundamental concepts were ""reinforcement learning"", giving a basic strategy for r choosing an appropriate motor command; ""modular architecture"", providing different visuo-motor transformations for different environments; and ""reliability of the internal model"", realizing an adaptive command selection according to the progress in learning. The behavior of the proposed model was examined in numerical experiments. Some related problems are discussed in relation to the results of psychological and numerical experiments.

Mathematical Model for the Tree Leaf Shape and Estimation of Leaf Mass

2012 ◽  
Vol 557-559 ◽  
pp. 2015-2020
Author(s):  
Yang Liu ◽  
Zhao Liu ◽  
Yu Zhang ◽  
Qian Yao Duan
Keyword(s):  
Mathematical Model ◽  
Numerical Experiments ◽  
Growth Regulation ◽  
Mass Density ◽  
Leaf Shape ◽  
Fibonacci Sequence ◽  
Leaf Mass ◽  
Proposed Model ◽  
Tree Leaf ◽  
The Relationship

The relationship between leaf shape and tree profile is discussed in this paper at first. Through analysis of Leonardo’s rule, Fibonacci sequence and growth regulation, we conclude that leaf shape is related to sunlight, tree profile, and the distribution of leaves. Then by constructing an integral equation of the leaf-mass density, a mathematical model is established to estimate leaf mass of a tree when the density nearly obeys gamma distribution. At last, some numerical experiments are presented to confirm the proposed model.

Motion Perception Based on Statistics of Phases

2014 ◽  
Vol 556-562 ◽  
pp. 3487-3491
Author(s):  
Hong Xia Wang ◽  
Bo Chen ◽  
Hao Xing Yang
Keyword(s):  
Phase Shift ◽  
Motion Perception ◽  
Numerical Experiments ◽  
Relative Phase ◽  
Motion Information ◽  
Phase Information ◽  
Image Series ◽  
Proposed Model ◽  
Perception Model ◽  
The Relationship

A motion perception model based on the relative phase is proposed in this paper. Firstly we use bilinear representation based on DTCW to derive the phase information on each subband for image series. The relationship between phase shift and edge position is theoretically proved and the distribution of relative phase is carefully explored. Numerical experiments show that the distribution of relative phase may make up the limitations of phases in providing motion information. The new proposed model is quite robust to changing contrast, complex edges and severe noise.

scholarly journals State-Level Students Grievance Support System

2020 ◽  
pp. 364-367
Author(s):  
Satheeswaran Venkatesan ◽  
Arjun R ◽  
Nidhin A ◽  
Pranav C. N2
Keyword(s):  
Support System ◽  
Web Application ◽  
State Level ◽  
Essential Factor ◽  
Web Based ◽  
Proposed Model ◽  
Manual Processing ◽  
The Relationship ◽  
Head Of Department ◽  
Web Based System

Students are the essential factor in an organization. The Scholar may feel dissatisfied with the service when he or she receives the delay of services. To beat this, we offer an optimized solution for the student grievances support system for improving the relationship between student and university by representing the model of e-complaint web-based system. The prevailing system has manual processing through committee, principal, head of department and college premises. This project overcomes the restrictions of the existing systems of complication of submitting a complaint and organizing it and it'll be a State-level support system. The proposed model is that the student has the ability to post a complaint easily and specifically using categories through our application and therefore the Admin are often ready to sort complains by supported keywords since the web application involves the utilization of keywords that are Students, Committee, Principal, University and Campus Which can be help us to provide the update data information through internet and It will helps to overcome the time process in an efficient way by acquire, store and process the data.

The Influence of Cognitive and Affective Reactions to Feedback on Subsequent Goals

2010 ◽  
Vol 15 (2) ◽  
pp. 121-131 ◽  
Author(s):  
Remus Ilies ◽  
Timothy A. Judge ◽  
David T. Wagner
Keyword(s):  
Performance Feedback ◽  
Business School ◽  
Structural Equation ◽  
Emotional Reactions ◽  
Equation Model ◽  
Proposed Model ◽  
And Performance ◽  
Dispositional Measure ◽  
The Relationship ◽  
Reactions To Feedback

This paper focuses on explaining how individuals set goals on multiple performance episodes, in the context of performance feedback comparing their performance on each episode with their respective goal. The proposed model was tested through a longitudinal study of 493 university students’ actual goals and performance on business school exams. Results of a structural equation model supported the proposed conceptual model in which self-efficacy and emotional reactions to feedback mediate the relationship between feedback and subsequent goals. In addition, as expected, participants’ standing on a dispositional measure of behavioral inhibition influenced the strength of their emotional reactions to negative feedback.

scholarly journals An analytical method reduces noise bias in motor adaptation analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Daniel H. Blustein ◽  
Ahmed W. Shehata ◽  
Erin S. Kuylenstierna ◽  
Kevin B. Englehart ◽  
Jonathon W. Sensinger
Keyword(s):  
Motor Planning ◽  
Motor Adaptation ◽  
Motor Command ◽  
Systematic Bias ◽  
Sources Of Information ◽  
Noise Masking ◽  
Stochastic Signal ◽  
Movement Data ◽  
Motor Error ◽  
Stochastic Signal Processing

AbstractWhen a person makes a movement, a motor error is typically observed that then drives motor planning corrections on subsequent movements. This error correction, quantified as a trial-by-trial adaptation rate, provides insight into how the nervous system is operating, particularly regarding how much confidence a person places in different sources of information such as sensory feedback or motor command reproducibility. Traditional analysis has required carefully controlled laboratory conditions such as the application of perturbations or error clamping, limiting the usefulness of motor analysis in clinical and everyday environments. Here we focus on error adaptation during unperturbed and naturalistic movements. With increasing motor noise, we show that the conventional estimation of trial-by-trial adaptation increases, a counterintuitive finding that is the consequence of systematic bias in the estimate due to noise masking the learner’s intention. We present an analytic solution relying on stochastic signal processing to reduce this effect of noise, producing an estimate of motor adaptation with reduced bias. The result is an improved estimate of trial-by-trial adaptation in a human learner compared to conventional methods. We demonstrate the effectiveness of the new method in analyzing simulated and empirical movement data under different noise conditions.

Modeling Capacity of Through Movement at Signalized Intersection Affected by Short Left-Turn Bay under Different Signal Settings

2021 ◽  
pp. 036119812110064
Author(s):  
Zihang Wei ◽  
Yunlong Zhang ◽  
Xiaoyu Guo ◽  
Xin Zhang
Keyword(s):  
Cycle Length ◽  
Signalized Intersections ◽  
Signalized Intersection ◽  
Essential Factor ◽  
Highway Capacity ◽  
Left Turn ◽  
Highway Capacity Manual ◽  
Proposed Model ◽  
Vehicle Demand ◽  
The One

Through movement capacity is an essential factor used to reflect intersection performance, especially for signalized intersections, where a large proportion of vehicle demand is making through movements. Generally, left-turn spillback is considered a key contributor to affect through movement capacity, and blockage to the left-turn bay is known to decrease left-turn capacity. Previous studies have focused primarily on estimating the through movement capacity under a lagging protected only left-turn (lagging POLT) signal setting, as a left-turn spillback is more likely to happen under such a condition. However, previous studies contained assumptions (e.g., omit spillback), or were dedicated to one specific signal setting. Therefore, in this study, through movement capacity models based on probabilistic modeling of spillback and blockage scenarios are established under four different signal settings (i.e., leading protected only left-turn [leading POLT], lagging left-turn, protected plus permitted left-turn, and permitted plus protected left-turn). Through microscopic simulations, the proposed models are validated, and compared with existing capacity models and the one in the Highway Capacity Manual (HCM). The results of the comparisons demonstrate that the proposed models achieved significant advantages over all the other models and obtained high accuracies in all signal settings. Each proposed model for a given signal setting maintains consistent accuracy across various left-turn bay lengths. The proposed models of this study have the potential to serve as useful tools, for practicing transportation engineers, when determining the appropriate length of a left-turn bay with the consideration of spillback and blockage, and the adequate cycle length with a given bay length.

scholarly journals Context-Aware Neural Machine Translation for Korean Honorific Expressions

Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1589
Author(s):  
Yongkeun Hwang ◽  
Yanghoon Kim ◽  
Kyomin Jung
Keyword(s):  
Machine Translation ◽  
Deep Neural Networks ◽  
Contextual Information ◽  
Context Aware ◽  
Neural Machine Translation ◽  
Translation Quality ◽  
Sentence Level ◽  
Proposed Model ◽  
The Given ◽  
The Relationship

Neural machine translation (NMT) is one of the text generation tasks which has achieved significant improvement with the rise of deep neural networks. However, language-specific problems such as handling the translation of honorifics received little attention. In this paper, we propose a context-aware NMT to promote translation improvements of Korean honorifics. By exploiting the information such as the relationship between speakers from the surrounding sentences, our proposed model effectively manages the use of honorific expressions. Specifically, we utilize a novel encoder architecture that can represent the contextual information of the given input sentences. Furthermore, a context-aware post-editing (CAPE) technique is adopted to refine a set of inconsistent sentence-level honorific translations. To demonstrate the efficacy of the proposed method, honorific-labeled test data is required. Thus, we also design a heuristic that labels Korean sentences to distinguish between honorific and non-honorific styles. Experimental results show that our proposed method outperforms sentence-level NMT baselines both in overall translation quality and honorific translations.

scholarly journals An Attention-Based Model Using Character Composition of Entities in Chinese Relation Extraction

Information ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 79 ◽  
Author(s):  
Xiaoyu Han ◽  
Yue Zhang ◽  
Wenkai Zhang ◽  
Tinglei Huang
Keyword(s):  
Language Processing ◽  
Large Scale ◽  
Named Entity Recognition ◽  
Relation Extraction ◽  
Entity Recognition ◽  
Additional Information ◽  
Named Entity ◽  
Proposed Model ◽  
The Relationship ◽  
Crucial Part

Relation extraction is a vital task in natural language processing. It aims to identify the relationship between two specified entities in a sentence. Besides information contained in the sentence, additional information about the entities is verified to be helpful in relation extraction. Additional information such as entity type getting by NER (Named Entity Recognition) and description provided by knowledge base both have their limitations. Nevertheless, there exists another way to provide additional information which can overcome these limitations in Chinese relation extraction. As Chinese characters usually have explicit meanings and can carry more information than English letters. We suggest that characters that constitute the entities can provide additional information which is helpful for the relation extraction task, especially in large scale datasets. This assumption has never been verified before. The main obstacle is the lack of large-scale Chinese relation datasets. In this paper, first, we generate a large scale Chinese relation extraction dataset based on a Chinese encyclopedia. Second, we propose an attention-based model using the characters that compose the entities. The result on the generated dataset shows that these characters can provide useful information for the Chinese relation extraction task. By using this information, the attention mechanism we used can recognize the crucial part of the sentence that can express the relation. The proposed model outperforms other baseline models on our Chinese relation extraction dataset.

Loyalty program in Africa: risk-seeking and risk-averse adventurers

2014 ◽  
Vol 69 (2) ◽  
pp. 137-157 ◽  
Author(s):  
Shogo Mlozi
Keyword(s):  
Consumer Behavior ◽  
Consumer Products ◽  
Loyalty Programs ◽  
Risk Averse ◽  
Loyalty Program ◽  
Content Type ◽  
Risk Seeking ◽  
Proposed Model ◽  
First Time ◽  
The Relationship

Purpose – This article aims to test the relationship between expected attractiveness-satisfaction-loyalty for international adventure tourists visiting Tanzania. The proposed model is based on travel consumer behavior theoretical constructs extracted from the literature. Design/methodology/approach – This article aims to test the relationship between expected attractiveness-satisfaction-loyalty for international adventure tourists visiting Tanzania. The proposed model is based on travel consumer behavior theoretical constructs extracted from the literature. Findings – The findings for overall model differed from the moderating factors of high risk, low risk, first-time visit and repeat visit. Also, the results are interesting when satisfaction is tested as a mediator. Practical implications – Practitioners could consider the fact that repeat visits may change tourists’ perceptions toward destination and may even increase their inclination to take on risks. This may impact innovation of consumer products in tourism. Also, policy makers could benefit on how loyalty programs can be developed to increase performance. Originality/value – The study offers specific strategic recommendations toward different groups of tourists (i.e. first-time, repeat visitors, risk averse, risk seeking) and proposes logic for setting up a loyalty program as a long-term strategy for success.

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