• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.47-54
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• 2023

For Bengali music emotion classification, deep learning models, particularly CNN and RNN are frequently used. But previous researches had the flaws of low accuracy and overfitting problem. In this research, attention-based Conv1D and BiGRU model is designed for music emotion classification and comparative experimentation shows that the proposed model is classifying emotions more accurate. We have proposed a Conv1D and Bi-GRU with the attention-based model for emotion classification of our Bengali music dataset. The model integrates attention-based. Wav preprocessing makes use of MFCCs. To reduce the dimensionality of the feature space, contextual features were extracted from two Conv1D layers. In order to solve the overfitting problems, dropouts are utilized. Two bidirectional GRUs networks are used to update previous and future emotion representation of the output from the Conv1D layers. Two BiGRU layers are conntected to an attention mechanism to give various MFCC feature vectors more attention. Moreover, the attention mechanism has increased the accuracy of the proposed classification model. The vector is finally classified into four emotion classes: Angry, Happy, Relax, Sad; using a dense, fully connected layer with softmax activation. The proposed Conv1D+BiGRU+Attention model is efficient at classifying emotions in the Bengali music dataset than baseline methods. For our Bengali music dataset, the performance of our proposed model is 95%.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.6
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• pp.273-283
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• 2016

In this paper, the effect of neurofeedback training program on attention ability of ADHD children is studied. The main concept of a neurofeedback training program is a robot control with brain wave. To do this, Mindset(neurosky, ltd) was used as a brain wave measurement and lego NXT was used to a robot kit. The developed brain wave training program has a 12 chapter. Students meet a problem situation and they invent and make a problem solving robot with NXT kits. After that, they control the their own robot by their brain wave. Developed program was applied to 8 student who live in chunan area. To monitor a change of attention ability, attention behavior checklist, K-CBCL, CTRS-R, ADS were used. These checklist were recorded with before and after the program. The result shows that student attention ability is increase after the program in the most of the checklist.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.496-498
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• 2023

Brain tumor segmentation problem has challenges in the tumor diversity of location, imbalance, and morphology. Attention mechanisms have recently been used widely to tackle medical segmentation problems efficiently by focusing on essential regions. In contrast, the fusion approaches enhance performance by merging mutual benefits from many models. In this study, we proposed a 3D dual fusion attention network to combine the advantages of fusion approaches and attention mechanisms by residual self-attention and local blocks. Compared to fusion approaches and related works, our proposed method has shown promising results on the BraTS 2018 dataset.

• The Journal of Korean Academic Society of Nursing Education
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• v.18 no.2
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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.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.3
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• pp.219-230
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• 2022

In implementing a robust automatic target recognition(ATR) system with synthetic aperture radar(SAR) imagery, one of the most important issues is accurate classification of target variants, which are the same targets with different serial numbers, configurations and versions, etc. In this paper, a deep learning network with channel attention modules is proposed to cope with the recognition problem for target variants based on the previous research findings that the channel attention mechanism selectively emphasizes the useful features for target recognition. Different from other existing attention methods, this paper employs the channel attention modules without dimensionality reduction along the channel direction from which direct correspondence between feature map channels can be preserved and the features valuable for recognizing SAR target variants can be effectively derived. Experiments with the public benchmark dataset demonstrate that the proposed scheme is superior to the network with other existing channel attention modules.

• Journal of the Korean Home Economics Association
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• v.41 no.7
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• pp.121-143
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• 2003

The purpose of this study was to show general trends in the psychological environment of family and problem behaviors perceived by adolescents and examine possible changes in such trends in accordance with the individual variables of adolescent, and then find out the effect of these variables on adolescents' problem behavior. The subject were 1374 adolescents of middle school in Busan(male 698, female 676). The main results were as follows : (1) General trends in the degree of parental monitoring showed that girls had more high than boys, and in the degree of family discord, boys showed more high than girls. In the degree of openness of parent-adolescent communication perceived by adolescents showed that girls had more open communication with mother than boys. Such trends in problem behaviors indicated that adolescents had the attention problem most. According to gender, girls had more problems in withdrawal, somatic complain, anxiety/depression, thought problems, attention problems, destructivity/identity, internalizing problems, total behavior problems in comparison to boys. Boys did delinquent behaviors more than girls. (2) For boys, the monthly income of their family, family discord, and the mother-adolescent communication have a significant direct effect on internalizing problems, externalizing problems and total behavior problems. Besides mother's employment and the type of family have a significant indirect effect on behavior problem. For girls, mother's employment, parental monitoring, family discord, and father-adolescent communication have a significant direct effect on internalizing problems. Mother's employment, family discord, mother-adolescent communication have a significant indirect effect on externalizing problems and total behavior problems. Bisides mother's employment, grade, the type of family, dating have a significant indirect effect on behavior problem. (3) The variables to have a significant influence on the parental monitoring showed as the monthly income of their family, dating, mother's employment, the type of family, the family discord showed as mother's employment on the parent-adolescent communication showed as the type of family. (4) Family discord was the most powerful predicator of problem behaviors of middle school students.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.33 no.1
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• pp.2-15
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• 2022

Objectives: Children with attention-deficit/hyperactivity disorder (ADHD) tend to be noisy and violate rules with their disruptive behaviors, resulting in greater difficulties with off-task behaviors and being at risk for social refusal. The visual activity schedule (VAS) intervention program is a frequently used method to teach multiple skills involving on-task, use of schedules, transition behaviors, social initiation, independent play skills, classroom skills, and academic skills. The current systematic review aimed to examine the efficacy of using VAS intervention in reducing problem behaviors in children with ADHD between 5 and 12 years of age. Methods: Systematic searches were conducted using two electronic databases (PubMed and Scopus) to identify relevant studies published in English between 2010 and 2020. Four studies met the inclusion criteria: two studies examined the effect of schedule-based tasks and the use of an iPad on classroom skills, while the other two examined randomized clinical trials (RCTs) of psychosocial treatment for ADHD inattentive type and a cross-sectional study examined the impact of the group size on task behavior and work productivity in children with ADHD. Results: The findings indicate that the interventions used in all four studies could lead to increased satisfaction among participants and parents, as well as a reduction in problem behavior. In terms of the research indicators, the RCT had low quality, while the others were of high quality. Conclusion: A larger number of studies and the ADHD clinical population would help to increase the generalizability of future reviews of treatments in this context.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.1-7
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• 2022

With the development of artificial intelligence, efforts to incorporate neuroscience mining with AI have increased. Neuroscience mining, also known as NSM, expands on this concept by combining computational neuroscience and business analytics. Using fNIRS (functional near-infrared spectroscopy)-based experiment dataset, we have investigated the potential of NSM in the context of the BPSC (business problem-solving creativity) prediction. Although BPSC is regarded as an essential business differentiator and a difficult cognitive resource to imitate, measuring it is a challenging task. In the context of NSM, appropriate methods for assessing and predicting BPSC are still in their infancy. In this sense, we propose a novel NSM method that systematically combines CNN, BiLSTM, and attention network for the sake of enhancing the BPSC prediction performance significantly. We utilized a dataset containing over 150 thousand fNIRS-measured data points to evaluate the validity of our proposed NSM method. Empirical evidence demonstrates that the proposed NSM method reveals the most robust performance when compared to benchmarking methods.

• Korean Journal of Child Studies
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• v.37 no.6
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• pp.69-82
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• 2016

Objective: The main purpose of this study was to investigate the effects of preschooler temperament and maternal postnatal depression, depression, and parenting stress on preschooler externalizing problem behavior. Methods: The participants consisted of 98 preschoolers (ages 4-5 years) and their mothers. The subjects completed the following questionnaires: Emotionality, Activity, and Sociability (EAS), Edinburgh Postnatal Depression Scale (EPDS), Center of Epidemiological Studies Depression Scale (CES-D), Parenting Stress Scale, Korean Child Behavior Checklist for Ages 1.5-5 (K-CBCL 1.5-5), and Social Competence and Behavior Evaluation Inventory Short Form (SCBE-30). The data were analyzed by t/F tests, Pearson's correlation analysis, and multiple regression analysis. Results and Conclusion: First, preschooler emotionality temperament had positive correlations with attention problems and aggression. Second, maternal depression and parenting stress had a positive correlation with preschooler externalizing problem behaviors. Third, maternal parenting stress had an effect on preschooler attention problems. Forth, preschooler emotional temperament and maternal parenting stress had an effect on preschooler aggression.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.4
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• pp.621-631
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• 2023

Adversarial training improves the robustness of deep neural networks for adversarial examples. However, the previous adversarial training method focuses only on the adversarial loss function, ignoring that even a small perturbation of the input layer causes a significant change in the hidden layer features. Consequently, the accuracy of a defended model is reduced for various untrained situations such as clean samples or other attack techniques. Therefore, an architectural perspective is necessary to improve feature representation power to solve this problem. In this paper, we apply an attention module that generates an attention map of an input image to a general model and performs PGD adversarial training upon the augmented model. In our experiments on the CIFAR-10 dataset, the attention augmented model showed higher accuracy than the general model regardless of the network structure. In particular, the robust accuracy of our approach was consistently higher for various attacks such as PGD, FGSM, and BIM and more powerful adversaries. By visualizing the attention map, we further confirmed that the attention module extracts features of the correct class even for adversarial examples.