• 한국심리학회지:학교
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• 제16권2호
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• pp.207-230
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• 2019

본 연구는 범불안 성향의 대학생을 대상으로 주의편향 및 범불안 증상에 대한 주의 피드백 인식 및 조절 훈련의 효과를 확인하였다. 범불안장애 척도(GAD-7) 10점 이상 또는 펜실베니아 걱정 질문지 척도(K-PSWQ) 56점 이상이며, 주의편향을 나타내는 범불안 성향의 대학생 31명을 선발하여 주의 피드백 인식 및 조절 훈련(Attention Feedback Awareness and Control Training, A-FACT) 집단(n = 11), 주의편향수정(Attention Bias Modification, ABM) 집단(n = 10) 및 활성 위약 통제(Active Placebo Control, APC) 집단(n = 10)에 무선할당하였다. A-FACT 집단은 탐침탐사과제를 이용한 주의편향수정 훈련 시, 개인의 기저반응시간(Baseline Neutral Response time, BNR)을 기준으로 편향 여부에 대한 피드백을 실시간으로 제공받았다. ABM 집단은 기존 ABM 절차와 동일하며, APC 집단은 주의편향을 감소시키기 위한 프로그램이라는 안내는 주어지지만 피드백이 주어지지 않는 탐침탐사과제를 실시하였다. 총 8회기로 구성되어, 주 2회로 4주간 진행되었다. 주의편향수정 훈련의 효과는 주의편향점수(Attention Bias Score, ABS)와 GAD-7, K-PSWQ 및 상태 및 특성 불안 검사(K-STAI) 점수 변화로 평가하였다. 반복측정 변량분석 결과, A-FACT 집단은 ABM 집단과 APC 집단에 비해 ABS가 유의하게 감소하였으며, GAD-7, K-PSWQ 및 K-STAI 점수도 유의하게 감소하였다. 이는 주의편향수정 훈련 시 편향에 대한 피드백을 통해 편향의 여부를 인식시키고 이를 통한 주의의 자기 조절적 통제가 주의편향 및 범불안장애 증상 경감에 효과적일 가능성을 시사한다.

• 영재교육연구
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• 제20권3호
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• pp.967-984
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• 2010

본 연구는 Feuerstein의 인지적 중재학습 경험이 영재아의 주의통제 및 주의전환에 미치는 효과를 알아보고자 하는데 그 목적이 있다. 초등학교 3학년 학생 중 지능검사와 창의성검사를 통해 영재아 40명을 선별하여 실험집단과 통제집단에 20명씩 무선 배정하였다. 실험 집단은 Feuerstein의 도구적 심화 프로그램을 연구의 목적에 맞게 수정한 인지적 중재학습 프로그램에 참여하였다. 연구결과, Feuerstein의 인지적 중재학습은 영재아의 선택적 주의집중, 자기통제력 및 지속적 주의집중 등 주의통제를 향상시키는 것으로 나타났다. 또한 주의전환 과제의 수행시간을 단축시킴으로써 영재아의 인지도식과 개념화 향상에도 기여하였다.

• 한국간호교육학회지
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• 제18권2호
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• pp.197-205
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• 2012

Purpose: This study aimed to demonstrate correlations among self-regulated learning, attention control and Yangseng, to clarify any differences depending on general characteristics and ultimately to understand factors affecting self-regulated learning of undergraduates. Methods: Data were collected for a month from April 1st, 2011. A total of 438 undergraduate nursing students of two universities in Chungbuk and Chungnam were surveyed by using a questionnaire about self-regulated learning, attention control and Yangseng. Results: Self-regulated learning of the subjects showed statistically significant correlations with their attention control (r=.302, p=.001) and Yangseng (r=.292, p=.001). In addition, self-regulated learning could be explained by attention control (${\beta}$=3.648, p=.001), Yangseng (${\beta}$=3.645, p=.001), perceived academic achievement levels (${\beta}$=.124, p=.018), or eating breakfast (${\beta}$=.102, p=.027). In the model, the variables explained self-regulated learning by 19.0%. Conclusion: Nursing instructors should encourage undergraduate nursing students to enhance their attention control so that they can improve their self-regulated learning abilities, which will eventually develop their problem solving skills. In addition, it was shown that self-regulated learning correlates with yangseng including eating a regular breakfast. Maintaining a desirable lifestyle is also essential for students to succeed in self-regulated learning.

• 동의신경정신과학회지
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• 제23권2호
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• pp.49-58
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• 2012

Objectives : The purpose of this study is to examine the effects of Mindfulness-based concentration qigong for children (MBCQ-C) in healthy children with subjective poor attention. Methods : This study examined the effects of MBCQ-C on healthy children with subjective poor attention, who vistied Korean medicine hospital neuropsychiatry outpatient clinic. The MBCQ-C was practiced with 11 participants, 2 of them quit in the middle of the program, and hence, they were excluded for data analysis. MBCQ-C consisted of 8 sessions, and each session took about 60 minutes. The outcome measurement was Frankfurter Aufmerksamkeits-Inventar (FAIR), which measured selective attention, self-control and sustained attention. Results : The results of this study showed that selective attention, and sustained attention were significantly improved. Self-control also improved, but without any statistical significance. These results indicate MBCQ-C was effective for the improvement of attention abilities, but self-control, including upper cognition area needs more consistent exercise. Conclusions : The MBCQ-C consisting of 8 sessions were shown to be an effective intervention in improving the attention abilities of healthy children with subjective poor attention.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권8호
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• pp.3791-3805
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• 2016

The visual attention mechanism includes 2 attention models, the bottom-up (B-U) and the top-down (T-D), the physiology of which have not yet been accurately described. In this paper, the visual attention mechanism is regarded as a Bayesian fusion process, and a visual attention model based on particle filter is proposed. Under certain particular assumed conditions, a calculation formula of Bayesian posterior probability is deduced. The visual attention fusion process based on the particle filter is realized through importance sampling, particle weight updating, and resampling, and visual attention is finally determined by the particle distribution state. The test results of multigroup images show that the calculation result of this model has better subjective and objective effects than that of other models.

• 생물정신의학
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• 제4권1호
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• pp.19-23
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• 1997

Attention is a phenomenon hard to define, but can be conceptualized as a mental function ranging from sustaining readiness to perceive stimuli to understanding the nature and value and selecting stimuli that are most relevant to the given situation. Manifestations of attention include vigilance, and focused, directed, selective, divided, and sustained attentions. While basic attentional tone is controlled by the interaction among reticular activating system, thalamus and prefrontal cortex, direction and selection of attention is controlled by neural circuits of prefrontal, posterior parietal, and limbic cortex. It is expected that understanding of attention and its neural control could provide answers to the relationship between pathophysiology and clinical symptoms of some major psychiatric disorders. More efforts are required to develop tools to assess more detailed and various aspects of attention in Korea.

• 한국학교보건학회지
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• 제23권2호
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• pp.237-245
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• 2010

Purpose: The purpose of this thesis was to examine the effects of social skills training program onto the children with tendency of attention-deficit hyperactivity disorder. Methods: This study used nonequivalent control group pre/post-test quasi-experimental research design. The subjects were 18 children with tendency of attention- deficit hyperactivity in D City. The subjects were divided into two groups, an experimental group of 8 children and a control group of 10. The program consisted of 20 sessions of 60 minutes per session, 5 days a weeks, for 4 weeks. The research tools included Conner's Teacher Rating Scales (CTRS) and Social Skills Rating System (SSRS). The collected data were analyzed using $x^2$ test, Mann-Whitney test on the SPSS 17.0 program. Results: a) the scores for cooperation, self-assertiveness, self-control and empathy increased significantly in the experimental group, compared to the control group. b) the scores for social skills increased significantly in the experimental group, compared to the control group. Conclusion: It appears that the social skills training program is a useful nursing intervention to improve the social skills for children with tendency of attention-deficit hyperactivity.

• 대한통합의학회지
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• 제9권2호
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• pp.183-192
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• 2021

Purpose : To investigate the degree of smartphone addiction among health-related college students, and to compare and analyze the effect of the degree of addiction on attention control and interpersonal support. Methods : 184 people who voluntarily participated and agreed to fill out the questionnaire were randomly sampled. The smartphone self-diagnosis scale was used to measure the degree of smartphone addiction, and the Attentional Control Questionnaire (ACQ) was used as a tool to measure the degree of attention control. In addition, the Interpersonal Support Evaluation List (ISEL) was used to measure the degree of interpersonal support. Results : In comparison of the degree of smartphone addiction according to the general characteristics of the subjects, there was no significant difference according to religion, major, and grade, but there was a significant difference in gender and daily use time of smartphones (p <.05). There was a significant difference in the degree of attention control according to the level of smartphone addiction (high risk, potential risk, general user group) (p <.05), but there was no significant difference in the degree of interpersonal support. Conclusion : The degree of smartphone addiction was relatively higher for women than for men, and users who used it for a long time per day were more addicted. It also showed that attention control was further reduced in highly addictive users.

• Journal of Information Processing Systems
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• 제17권2호
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• pp.242-252
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• 2021

Following the intuition that the local information in time instances is hardly incorporated into the posterior sequence in long short-term memory (LSTM), this paper proposes an attention augmented mechanism for fault diagnosis of the complex chemical process data. Unlike conventional fault diagnosis and classification methods, an attention mechanism layer architecture is introduced to detect and focus on local temporal information. The augmented deep network results preserve each local instance's importance and contribution and allow the interpretable feature representation and classification simultaneously. The comprehensive comparative analyses demonstrate that the developed model has a high-quality fault classification rate of 95.49%, on average. The results are comparable to those obtained using various other techniques for the Tennessee Eastman benchmark process.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권3호
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• pp.721-739
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• 2023

Rating prediction is an important issue in recommender systems, and its accuracy affects the experience of the user and the revenue of the company. Traditional recommender systems use Factorization Machinesfor rating predictions and each feature is selected with the same weight. Thus, there are problems with inaccurate ratings and limited data representation. This study proposes a deep recommendation model based on self-attention Factorization (SAFMR) to solve these problems. This model uses Convolutional Neural Networks to extract features from user and item reviews. The obtained features are fed into self-attention mechanism Factorization Machines, where the self-attention network automatically learns the dependencies of the features and distinguishes the weights of the different features, thereby reducing the prediction error. The model was experimentally evaluated using six classes of dataset. We compared MSE, NDCG and time for several real datasets. The experiment demonstrated that the SAFMR model achieved excellent rating prediction results and recommendation correlations, thereby verifying the effectiveness of the model.