• Title/Summary/Keyword: brain-based learning

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A Design of Super Value based Flexible KEB Reasoning System (Super Value 기반의 유연한 KEB 추론 시스템의 설계)

  • Shim, JeongYon
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.5
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    • pp.137-143
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    • 2013
  • In recent years there have been many efforts for changing from machine oriented technology to human oriented technology gradually. In the research of Intelligent system, the previous simple learning and reasoning methods are also changing to human like processing, namely the direction of implementing humanity. Especially as Neuro Engineering research is getting active, the studies on application of brain function are increasing in the engineering aspects. In this paper, we defined Super Value as a concept which reflect the higher value of 'viewpoint' and proposed flexible KEB(Knowledge-Emotion Binding) System. The system has a hierarchical structure which consists of Main level and Super level for flexibility and it is designed for having the function of extracting KEB Threads by Reasoning mechanism.

DNA (Data, Network, AI) Based Intelligent Information Technology (DNA (Data, Network, AI) 기반 지능형 정보 기술)

  • Youn, Joosang;Han, Youn-Hee
    • KIPS Transactions on Computer and Communication Systems
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    • v.9 no.11
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    • pp.247-249
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    • 2020
  • In the era of the 4th industrial revolution, the demand for convergence between ICT technologies is increasing in various fields. Accordingly, a new term that combines data, network, and artificial intelligence technology, DNA (Data, Network, AI) is in use. and has recently become a hot topic. DNA has various potential technology to be able to develop intelligent application in the real world. Therefore, this paper introduces the reviewed papers on the service image placement mechanism based on the logical fog network, the mobility support scheme based on machine learning for Industrial wireless sensor network, the prediction of the following BCI performance by means of spectral EEG characteristics, the warning classification method based on artificial neural network using topics of source code and natural language processing model for data visualization interaction with chatbot, related on DNA technology.

The Study of the Disability Education Experience of the Mothers for their Children with Brain Lesions - Hermeneutic Grounded Theory Methodology - (중증뇌병변장애인 자녀를 둔 어머니들의 장애자녀 교육경험에 관한 연구 -해석학적 질적연구-)

  • Kang, Sun Kyung;Choi, Yoon
    • 재활복지
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    • v.20 no.4
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    • pp.79-106
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    • 2016
  • This study examined the meanings of the disability education of the mothers who reared their children with brain lesions. For this purpose, Rennie's hermeneutic grounded theory was applied and the consented 7 mothers participated in this study. With the in-depth interviews, 53 meaning units, 16 subordinate categories and 7 hermeneutic categories were classified. These 7 hermeneutic categories were 'wailing miserably everyday', 'social mobilization of the surroundings', 'straight forward', 'smash rock with the eggs', 'looking at a faraway', 'learning together' and 'subjectivation of disability education.' The experience of disabled children education process was concurrent experience of frustration and hoping that moving toward a big hope through the resignation stage, the chasing stage, the vision stage, the challenge stage, and the small achievement stage. Repetitive common patterns of behavior revealed three types: wishy-washy type, realistic-strategy type, and indomitable-challenge type. Moreover, the core category of educational experience was concluded to be 'a pedagogical process of turning despair from severe disabilities into hope through education.' Based on the analysis results, concrete intervention plans for social welfare practice were suggested to support the disabled children's lives with high quality of education.

A Review of the Neurocognitive Mechanisms for Mathematical Thinking Ability (수학적 사고력에 관한 인지신경학적 연구 개관)

  • Kim, Yon Mi
    • Korean Journal of Cognitive Science
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    • v.27 no.2
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    • pp.159-219
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    • 2016
  • Mathematical ability is important for academic achievement and technological renovations in the STEM disciplines. This study concentrated on the relationship between neural basis of mathematical cognition and its mechanisms. These cognitive functions include domain specific abilities such as numerical skills and visuospatial abilities, as well as domain general abilities which include language, long term memory, and working memory capacity. Individuals can perform higher cognitive functions such as abstract thinking and reasoning based on these basic cognitive functions. The next topic covered in this study is about individual differences in mathematical abilities. Neural efficiency theory was incorporated in this study to view mathematical talent. According to the theory, a person with mathematical talent uses his or her brain more efficiently than the effortful endeavour of the average human being. Mathematically gifted students show different brain activities when compared to average students. Interhemispheric and intrahemispheric connectivities are enhanced in those students, particularly in the right brain along fronto-parietal longitudinal fasciculus. The third topic deals with growth and development in mathematical capacity. As individuals mature, practice mathematical skills, and gain knowledge, such changes are reflected in cortical activation, which include changes in the activation level, redistribution, and reorganization in the supporting cortex. Among these, reorganization can be related to neural plasticity. Neural plasticity was observed in professional mathematicians and children with mathematical learning disabilities. Last topic is about mathematical creativity viewed from Neural Darwinism. When the brain is faced with a novel problem, it needs to collect all of the necessary concepts(knowledge) from long term memory, make multitudes of connections, and test which ones have the highest probability in helping solve the unusual problem. Having followed the above brain modifying steps, once the brain finally finds the correct response to the novel problem, the final response comes as a form of inspiration. For a novice, the first step of acquisition of knowledge structure is the most important. However, as expertise increases, the latter two stages of making connections and selection become more important.

Motor Imagery based Brain-Computer Interface for Cerebellar Ataxia (소뇌 운동실조 이상 환자를 위한 운동상상 기반의 뇌-컴퓨터 인터페이스)

  • Choi, Young-Seok;Shin, Hyun-Chool;Ying, Sarah H.;Newman, Geoffrey I.;Thakor, Nitish
    • Journal of the Korean Institute of Intelligent Systems
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    • v.24 no.6
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    • pp.609-614
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    • 2014
  • Cerebellar ataxia is a steadily progressive neurodegenerative disease associated with loss of motor control, leaving patients unable to walk, talk, or perform activities of daily living. Direct motor instruction in cerebella ataxia patients has limited effectiveness, presumably because an inappropriate closed-loop cerebellar response to the inevitable observed error confounds motor learning mechanisms. Recent studies have validated the age-old technique of employing motor imagery training (mental rehearsal of a movement) to boost motor performance in athletes, much as a champion downhill skier visualizes the course prior to embarking on a run. Could the use of EEG based BCI provide advanced biofeedback to improve motor imagery and provide a "backdoor" to improving motor performance in ataxia patients? In order to determine the feasibility of using EEG-based BCI control in this population, we compare the ability to modulate mu-band power (8-12 Hz) by performing a cued motor imagery task in an ataxia patient and healthy control.

A Quality Identification System for Molding Parts Using HTM-Based Sound Recognition (HTM 기반의 소리 연식을 이용한 부품의 양.불량 판별 시스템)

  • Bae, Sun-Gap;Han, Chang-Young;Seo, Dae-Ho;Kim, Sung-Jin;Bae, Jong-Min;Kang, Hyun-Syug
    • Journal of Korea Multimedia Society
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    • v.13 no.10
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    • pp.1494-1505
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    • 2010
  • A variety of sounds take place in medium and small-sized manufactories producing many kinds of parts in a small quantity with one press. We developed the identification system for the quality of parts using HTM(Hierarchical Temporal Memory)-based sound recognition. HTM is the theory that the operation principle of human brain's neocortex is applied to computer, suggested by Jeff Hopkins. This theory memorizes temporal and spatial patterns hierarchically about the real world, which is known for its cognitive power superior to the previous recognition technologies in many cases. By applying the HTM model to the sound recognition, we developed the identification system for the quality of molding parts. In order to verify its performance we recorded the various sounds at the moment of producing parts in the real factory, constructed the HTM network of sound, and then identified the quality of parts by repeating learning and training. It reveals that this system gets an excellent and accurate results at the noisy factory.

Development of EEG Signals Measurement and Analysis Method based on Timbre (음색 기반 뇌파측정 및 분석기법 개발)

  • Park, Seung-Min;Lee, Young-Hwan;Ko, Kwang-Eun;Sim, Kwee-Bo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.3
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    • pp.388-393
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    • 2010
  • Cultural Content Technology(CT, Culture Technology) for the development of cultural industry and the commercialization of technology, cultural contents, media, mount, pass the value chain process and increase the added value of cultural products that are good for all forms of intangible technology. In the field of Culture Technology, Music by analyzing the characteristics of the development of a variety of applications has been studied. Associated with EEG measures and the results of their research in response to musical stimuli are used to detect and study is getting attention. In this paper, the musical stimuli in EEG signals by amplifying the corresponding reaction to the averaging method, ERP (Event-Related Potentials) experiments based on the process of extracting sound methods for removing noise from the ICA algorithm to extract the tone and noise removal according to the results are applied to analyze the characteristics of EEG.

A Study on Image Recognition based on the Characteristics of Retinal Cells (망막 세포 특성에 의한 영상인식에 관한 연구)

  • Cho, Jae-Hyun;Kim, Do-Hyeon;Kim, Kwang-Baek
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.11
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    • pp.2143-2149
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    • 2007
  • Visual Cortex Stimulator is among artificial retina prosthesis for blind man, is the method that stimulate the brain cell directly without processing the information from retina to visual cortex. In this paper, we propose image construction and recognition model that is similar to human visual processing by recognizing the feature data with orientation information, that is, the characteristics of visual cortex. Back propagation algorithm based on Delta-bar delta is used to recognize after extracting image feature by Kirsh edge detector. Various numerical patterns are used to analyze the performance of proposed method. In experiment, the proposed recognition model to extract image characteristics with the orientation of information from retinal cells to visual cortex makes a little difference in a recognition rate but shows that it is not sensitive in a variety of learning rates similar to human vision system.

Myelin Content in Mild Traumatic Brain Injury Patients with Post-Concussion Syndrome: Quantitative Assessment with a Multidynamic Multiecho Sequence

  • Roh-Eul Yoo;Seung Hong Choi;Sung-Won Youn;Moonjung Hwang;Eunkyung Kim;Byung-Mo Oh;Ji Ye Lee;Inpyeong Hwang;Koung Mi Kang;Tae Jin Yun;Ji-hoon Kim;Chul-Ho Sohn
    • Korean Journal of Radiology
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    • v.23 no.2
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    • pp.226-236
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    • 2022
  • Objective: This study aimed to explore the myelin volume change in patients with mild traumatic brain injury (mTBI) with post-concussion syndrome (PCS) using a multidynamic multiecho (MDME) sequence and automatic whole-brain segmentation. Materials and Methods: Forty-one consecutive mTBI patients with PCS and 29 controls, who had undergone MRI including the MDME sequence between October 2016 and April 2018, were included. Myelin volume fraction (MVF) maps were derived from the MDME sequence. After three dimensional T1-based brain segmentation, the average MVF was analyzed at the bilateral cerebral white matter (WM), bilateral cerebral gray matter (GM), corpus callosum, and brainstem. The Mann-Whitney U-test was performed to compare MVF and myelin volume between patients with mTBI and controls. Myelin volume was correlated with neuropsychological test scores using the Spearman rank correlation test. Results: The average MVF at the bilateral cerebral WM was lower in mTBI patients with PCS (median [interquartile range], 25.2% [22.6%-26.4%]) than that in controls (26.8% [25.6%-27.8%]) (p = 0.004). The region-of-interest myelin volume was lower in mTBI patients with PCS than that in controls at the corpus callosum (1.87 cm3 [1.70-2.05 cm3] vs. 2.21 cm3 [1.86-3.46 cm3]; p = 0.003) and brainstem (9.98 cm3 [9.45-11.00 cm3] vs. 11.05 cm3 [10.10-11.53 cm3]; p = 0.015). The total myelin volume was lower in mTBI patients with PCS than that in controls at the corpus callosum (0.45 cm3 [0.39-0.48 cm3] vs. 0.48 cm3 [0.45-0.54 cm3]; p = 0.004) and brainstem (1.45 cm3 [1.28-1.59 cm3] vs. 1.54 cm3 [1.42-1.67 cm3]; p = 0.042). No significant correlation was observed between myelin volume parameters and neuropsychological test scores, except for the total myelin volume at the bilateral cerebral WM and verbal learning test (delayed recall) (r = 0.425; p = 0.048). Conclusion: MVF quantified from the MDME sequence was decreased at the bilateral cerebral WM in mTBI patients with PCS. The total myelin volumes at the corpus callosum and brainstem were decreased in mTBI patients with PCS due to atrophic changes.

The Effects of Virtual Competitors on AR (Augmented Reality) Home Training System: Focusing on Immersion, Perceived Competition, and Learning Motivation (증강현실을 활용한 홈 트레이닝에서 가상 참여자의 영향: 몰입, 인지된 경쟁, 그리고 정보 습득의 욕구를 중심으로)

  • Choi, Sungho;Lee, Wonouk;Kim, Hyunju;Won, Jongseo;Lee, Jeehang;Lee, Yeonjoo;Kim, Jinwoo
    • Science of Emotion and Sensibility
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    • v.20 no.3
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    • pp.119-130
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    • 2017
  • The purpose of the study is discovering the effects of virtual competitors on user in AR (Augment Reality) home training system. Specifically, the current research examined their effects on immersion, perceived competition, and leaning motivation. The paper tested three unexplored relationship. First, introducing virtual competitors in home training system will enhance user's immersion. Second, presenting virtual competitors in home training system will increase user's perceived competition. Third, virtual competitors in home training system will raise user's learning motivation. For empirical analysis, we developed home training system, which could check and give feedback automatically, based on user's posture. Using this AR home training system, the study empirically shows how and why virtual competitors affect users. The results give implications not only on service design; but also on the idea that virtual other could affect user's behavior.