scholarly journals Subliminal Calibration for Machine Operation

2012 ◽  
Vol 16 (1) ◽  
pp. 108-116 ◽  
Author(s):  
Hiroshi Igarashi ◽  
Keyword(s):  
Human Learning ◽  
Learning Ability ◽  
Reactive Force ◽  
Operation Performance ◽  
Machine System ◽  
Machine Operation ◽  
Machine Dynamics

This paper proposes a skill assist technique without having the operator to be aware of it. Heretofore, many operation assists in a human-machine system has added artificial force in human operation input such as reactive force from obstacles. Such an approach is suitable in a particular task as simulated by the designer, because it can improve safety and efficiency, but is simultaneously hindering human learning ability. The proposed method will correct the machine dynamics of the operation subject subliminally, meaning that the operator will not be aware that it is being altered. Henceforth, it will be possible to enhance operability, without having to prevent the human learning ability. As a result of a verification experiment on 20 test subjects, it has been clarified that it is possible to enhance the operation performance without the operators knowing of the assist.

Study of Human Driving Skill in Expected and Guided Conditions

2015 ◽  
Vol 73 (6) ◽  
Author(s):  
Amirah ‘Aisha Badrul Hisham ◽  
Mohamad Hafis Izran Ishak ◽  
Ruzairi Abdul Rahim ◽  
Nurul Hawani Idris
Keyword(s):  
Human Activities ◽  
Human Subjects ◽  
Index Formula ◽  
Crucial Issue ◽  
Machine System ◽  
Machine Operation ◽  
Driving Skill ◽  
Recent Developments ◽  
Human Skills ◽  
Definition Of

This day, Human Machine System (HMS) consider being a proven technology, which has gained an important role in various human activities. One of the most recent developments in this area is Human Adaptive Mechatronics (HAM) approach for enhancing human skills. This approach therefore is different compared to an ordinary HMS, in terms of its ability to adapt to changes in its environment and in the human changing level of skills. The crucial issue in HAM is in evaluating the human skills level on machine operation. In this paper, a skill index to quantify the performance of human drivers is studied in expected and guided conditions. The experiments are carried out on human subjects in normal driving. From this experiment, a new skill index formula is proposed based on the logical conditions and the definition of skill in HAM.

scholarly journals INFORMATION AND MEMORY-BASED ANALYSIS FOR DECODING OF THE HUMAN LEARNING BETWEEN NORMAL AND VIRTUAL REALITY (VR) CONDITIONS

Fractals ◽  
2021 ◽  
Vol 29 (03) ◽  
pp. 2150163
Author(s):  
HAMIDREZA NAMAZI ◽  
MOHAMMAD HOSSEIN BABINI ◽  
KAMIL KUCA ◽  
ONDREJ KREJCAR
Keyword(s):  
Virtual Reality ◽  
Shannon Entropy ◽  
Mathematical Analysis ◽  
Strong Correlation ◽  
Hurst Exponent ◽  
Human Learning ◽  
Learning Ability ◽  
Eeg Signals ◽  
2D And 3D ◽  
Electroencephalogram Eeg

In this paper, we investigated the learning ability of students in normal versus virtual reality (VR) watching of videos by mathematical analysis of electroencephalogram (EEG) signals. We played six videos in the 2D and 3D modes for nine subjects and calculated the Shannon entropy of recorded EEG signals to investigate how much their embedded information changes between these modes. We also calculated the Hurst exponent of EEG signals to compare the changes in the memory of signals. The analysis results showed that watching the videos in a VR condition causes greater information and memory in EEG signals. A strong correlation was obtained between the increment of information and memory of EEG signals. These increments also have been verified based on the answers that subjects gave to the questions about the content of videos. Therefore, we can say that when subjects watch a video in a VR condition, more information is transferred to their brains that cause increments in their memory.

Feedback and human learning: Preliminary insights from disengaged students

2021 ◽  
pp. 1-13
Author(s):  
Kongkiti Phusavat ◽  
Zbigniew Pastuszak ◽  
Achmad Nizar Hidayanto ◽  
Jukka Majava
Keyword(s):  
Human Learning ◽  
Business Community ◽  
Learning Ability ◽  
Traditional Practices ◽  
Constructive Feedback ◽  
External Feedback ◽  
Indirect Feedback ◽  
Traditional Paradigm

BACKGROUND: How to reconnect the disengaged learners has been a major challenge for human learning. Motivating the disengaged learners through traditional interventions has not been effective. OBJECTIVE: The study aims to examine whether feedback from an external unit would be more persuasive for the disengaged learners. The perception on a lack of learning stems from poor attitude of learning, poor behavior, laziness, and lack of learning ability and attention. METHODS: A foreign business community has collaborated with two Bangkok Metropolitan Administration schools since 2016 on creating constructive and indirect feedback. There were 337 students from both schools participated in the survey. 163 students participated in the revised practices while 174 students attended the traditional practices. RESULTS: The results show the gap between the two groups on the effects from constructive and indirect feedback. The disengaged students from the revised pedagogy show that they are attracted to constructive feedback and indirect feedback more. CONCLUSIONS: The findings show that, unlike the traditional paradigm, the disengaged students are perceptive to external feedback. The findings show some consistency with previous studies. Integrating external feedback can attract the attention from the disengaged students which could potentially contribute to human learning.

Human Adaptive Calibration for Machine Operation Without Awareness

2008 ◽  
Vol 20 (4) ◽  
pp. 595-601 ◽  
Author(s):  
Hiroshi Igarashi ◽  
Keyword(s):  
Scientific Knowledge ◽  
Dynamics Model ◽  
Machine Model ◽  
Machine Operation ◽  
Machine Dynamics ◽  
Adaptive Calibration ◽  
Mobile Vehicle

Optimum human-machine operation is defined as when a operated machine with “human calculated dynamics model” coincides with its “machine dynamics.” Based on this definition, we propose calibration that brings the machine dynamics closer to the human-calculated machine model. Operators tend to learn dynamics without awareness during machine operation, so changes in machine dynamics appear to pose problems that both make operators uncomfortable and hinder their learning. We propose calibration for changes in machine dynamics without operator awareness, by quantifying perception based on cognitive scientific knowledge. We applied this calibration to a task involving the maneuvering of a mobile vehicle.

scholarly journals The structure of hippocampal trisynaptic pathway relates to rapid category learning in humans

2021 ◽  
Author(s):  
Margaret L Schlichting ◽  
Melisa Gumus ◽  
Teresa Zhu ◽  
Michael L Mack
Keyword(s):  
White Matter ◽  
Category Learning ◽  
Diffusion Weighted Imaging ◽  
Human Learning ◽  
General Information ◽  
Learning Ability ◽  
Information Flows ◽  
Learning Mechanisms ◽  
Specific Association

Prior work suggests that complementary white matter pathways within the hippocampus differentially support learning of specific versus general information. In particular, while the trisynaptic pathway (TSP) rapidly forms memories for specific experiences, the monosynaptic pathway (MSP) slowly learns generalities. However, despite the theorized significance of such circuitry, characterizing how information flows within hippocampus (HPC) to support learning in humans remains a challenge. We leveraged diffusion-weighted imaging as a proxy for individual differences in TSP and MSP white matter structure and related it to category learning ability. We hypothesized that learning to categorize the "exception" items that deviated from category rules would benefit from TSP-supported mnemonic specificity. Participant-level estimates of TSP and MSP integrity were constructed from HPC subfield connectomes of white matter streamline density. Consistent with theories of TSP-supported learning mechanisms, we found a specific association between TSP integrity and exception learning. These results highlight the significant role of HPC circuitry in complex human learning.

scholarly journals A Study on Human Learning Ability during Classification of Motion and Colour Visual Cues and Their Combination

2021 ◽  
Vol 21 (1) ◽  
pp. 73-86
Author(s):  
Albena Tchamova ◽  
Jean Dezert ◽  
Nadejda Bocheva ◽  
Pavlina Konstantinova ◽  
Bilyana Genova ◽  
...  
Keyword(s):  
Visual Cues ◽  
Human Learning ◽  
Learning Curves ◽  
Learning Ability ◽  
Stimulus Information ◽  
Relevant Stimulus ◽  
Group Behaviour ◽  
Human Individual ◽  
Effect Of Age

Abstract The paper presents a study on the human learning process during the classification of stimuli, defined by motion and color visual cues and their combination. Because the classification dimension and the features that define each category are uncertain, we model the learning curves using Bayesian inference and more precisely the Normalized Conjunctive Consensus rule, and also on the base of the more efficient probabilistic Proportional Conflict Redistribution rule No 5 (pPCR5) defined within Dezert-Smarandache Theory (DSmT) of plausible and paradoxical reasoning. Our goal is to study how these rules succeed to model consistently both: human individual and group behaviour during the learning of the associations between the stimuli and the responses in categorization tasks varying by the amount of relevant stimulus information. The effect of age on this process is also evaluated.

Personal Factors in Human Learning: II. Learning Ability and Subjective Stress

1973 ◽  
Vol 88 (1) ◽  
pp. 87-91 ◽  
Author(s):  
Aldred H. Neufeldt ◽  
Patricia Raulston ◽  
Gladys Peterson
Keyword(s):  
Human Learning ◽  
Learning Ability ◽  
Personal Factors ◽  
Subjective Stress

Models of comets with strongly variable nongravitational effects

1999 ◽  
Vol 173 ◽  
pp. 381-387
Author(s):  
M. Królikowska ◽  
G. Sitarski ◽  
S. Szutowicz
Keyword(s):  
Cometary Nucleus ◽  
Spin Axis ◽  
Reactive Force ◽  
Orbital Elements ◽  
Cometary Nuclei ◽  
Short Period ◽  
Basic Parameters ◽  
Polar Radius ◽  
Cometary Activity ◽  
Nongravitational Effects

AbstractThe nongravitational motion of five “erratic” short-period comets is studied on the basis of published astrometric observations. We present the precession models which successfully link all the observed apparitions of the comets: 21P/Giacobini-Zinner, 31P/Schwassmann-Wachmann 2, 32P/Comas Solá, 37P/Forbes, and 43P/Wolf-Harrington. We used the Sekanina's forced precession model of the rotating cometary nucleus to include the nongravitational terms into equations of the comet's motion. Values of six basic parameters (four connected with the rotating comet nucleus and two describing the precession of spin-axis of the nucleus) have been determined along the orbital elements from positional observations of the comets. The solutions were derived with additional assumptions which introduce instantaneous changes of modulus of reactive force,Aand of maximum of cometary activity with respect to perihelion time. The present precession models impose some contraints on sizes and rotational periods of cometary nuclei. According to our solutions the nucleus of 21P/Giacobini-Zinner with oblateness along the spin-axis of about 0.32 (equatorial to polar radius of 1.46) is the most oblate among five investigated comets.

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