• The Journal of Pediatrics of Korean Medicine
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• v.23 no.3
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• pp.241-262
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• 2009

Objectives This study is designed to investigate the effects of Jujadokseo-hwan on the brain ability and inducing oxidative stresses. Methods We measured the changes of regional cerebral blood flow and mean arterial blood pressure. Then we analyzed histological examination, immunohistochemistric response and anti-oxidant activity of Jujadokseo-hwan. Results 1. Treatment of Jujadokseo-hwan significantly increased regional cerebral blood flow but decreased mean arterial blood pressure. 2. Treatment of Jujadokseo-hwan-induced increase of regional cerebral blood flow was significantly inhibited by pretreatment with indomethacin (1 mg/kg, i.p.), an inhibitor of cyclooxygenase. 3. In histological examination through TTC stain, group I was no change, but group II showed that discolored in the most cortical part. Group III showed that decreased discolor in the cortical part. 4. In immunohistochemistric response of BDNF, group II showed that lower response effect. Group III showed that increase response effect. 5. Treatment of Jujadokseo-hwan increased proliferation rates of Glial cell effectively 6. Treatment of Jujadokseo-hwan accelerated proliferation rates of C6 cells in vitro. In addition, protective effects on cell death induced by paraquat, rotenone and hydrogen peroxide. In addition, activity of SOD were increased by treatment with Jujadokseo-hwan. Conclusions In conclusion, Jujadokseo-hwan can improve of the brain ability, learning ability, memory ability and induce ischemic brain injuries.

• Journal of the Korean Society of Physical Medicine
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• v.7 no.1
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• pp.11-20
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• 2012

Purpose : This study is intended to examine the repetitive transcranial magnetic stimulation on cognitive function in the focal ischemic stroke rat model. Methods : This study selected 30 Sprague-Dawley rats of 8 weeks. The groups were divided into two groups and assigned 15 rats to each group. Control group: Non-treatment after injured by focal ischemic stroke; Experimental group: application of repetitive transcranial magnetic stimulation(0.1 Tesla, 25 Hz, 20 min/time, 2 times/day, 5 days/2 week) after injured by focal ischemic stroke. To assess the effect of rTMS, the passive avoidance test, spatial learning and memory ability test were analyzed at the pre, 1 day, $7^{th}$ day, $14^{th}$ day and immunohistochemistric response of BDNF were analyzed in the hippocampal dentate gyrus at $7^{th}$ day, $14^{th}$ day. Results : In passive avoidance test, the outcome of experimental group was different significantly than the control group at the $7^{th}$ day, $14^{th}$ day. In spatial learning and memory ability test, the outcome of experimental group was different significantly than the control group at the $7^{th}$ day, $14^{th}$ day. In immunohistochemistric response of BDNF in the hippocampal dentate gyrus, experimental groups was more increased than control group. Conclusion : These result suggest that improved cognitive function by repetitive transcranial magnetic stimulation after focal ischemic stroke is associated with dynamically altered expression of BDNF in hippocampal dentate gyrus and that is related with synaptic plasticity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3868-3888
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• 2022

A widely used social networking service like Twitter has the ability to disseminate information to large groups of people even during a pandemic. At the same time, it is a convenient medium to share irrelevant and unverified information online and poses a potential threat to society. In this research, conventional machine learning algorithms are analyzed to classify the data as either non-rumor data or rumor data. Machine learning techniques have limited tuning capability and make decisions based on their learning. To tackle this problem the authors propose a deep learning-based Rumor Detection Neural Network model to predict the rumor tweet in real-world events. This model comprises three layers, AttCNN layer is used to extract local and position invariant features from the data, AttBi-LSTM layer to extract important semantic or contextual information and HPOOL to combine the down sampling patches of the input feature maps from the average and maximum pooling layers. A dataset from Kaggle and ground dataset #gaja are used to train the proposed Rumor Detection Neural Network to determine the veracity of the rumor. The experimental results of the RDNN Classifier demonstrate an accuracy of 93.24% and 95.41% in identifying rumor tweets in real-time events.

• Journal of Information Processing Systems
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• v.20 no.3
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• pp.375-390
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• 2024

Edge computing architecture has effectively alleviated the computing pressure on cloud platforms, reduced network bandwidth consumption, and improved the quality of service for user experience; however, it has also introduced new security issues. Existing anomaly detection methods in big data scenarios with cloud-edge computing collaboration face several challenges, such as sample imbalance, difficulty in dealing with complex network traffic attacks, and difficulty in effectively training large-scale data or overly complex deep-learning network models. A lightweight deep-learning model was proposed to address these challenges. First, normalization on the user side was used to preprocess the traffic data. On the edge side, a trained Wasserstein generative adversarial network (WGAN) was used to supplement the data samples, which effectively alleviates the imbalance issue of a few types of samples while occupying a small amount of edge-computing resources. Finally, a trained lightweight deep learning network model is deployed on the edge side, and the preprocessed and expanded local data are used to fine-tune the trained model. This ensures that the data of each edge node are more consistent with the local characteristics, effectively improving the system's detection ability. In the designed lightweight deep learning network model, two sets of convolutional pooling layers of convolutional neural networks (CNN) were used to extract spatial features. The bidirectional long short-term memory network (BiLSTM) was used to collect time sequence features, and the weight of traffic features was adjusted through the attention mechanism, improving the model's ability to identify abnormal traffic features. The proposed model was experimentally demonstrated using the NSL-KDD, UNSW-NB15, and CIC-ISD2018 datasets. The accuracies of the proposed model on the three datasets were as high as 0.974, 0.925, and 0.953, respectively, showing superior accuracy to other comparative models. The proposed lightweight deep learning network model has good application prospects for anomaly traffic detection in cloud-edge collaborative computing architectures.

• Journal of vocational education research
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• v.29 no.3
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• pp.133-156
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• 2010

This study examines corporate support in learning on individual participation in learning and organizational learning. For this purpose, First, what does corporate support in learning affect individual participation in learning? Second, what does corporate support in learning and individual participation influence organizational learning? This study analyzed 1,268 employees at 139 companies. Sample sizes averaged about 9.22 employee per corporate. This paper used statistical method of hierarchical linear model. Above all, the findings show that corporate support in both formal and informal learning has meaningful effect on individual participation in formal learning and relationship. The findings reveal that corporate support in formal learning has influence on capacity, organizational memory, learning competency, adaptation to environment except sharing value. Furthermore, individual participation in learning has positive effect of increased organizational learning in all areas. In particular, it is shown that participation in informal relationship plays an important role to improve individuals' organizational learning ability.

• Biomolecules & Therapeutics
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• v.24 no.3
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• pp.328-337
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• 2016

We examined whether wogonin (WO) improved hippocampal neuronal activity, behavioral alterations and cognitive impairment, in rats induced by administration of trimethyltin (TMT), an organotin compound that is neurotoxic to these animals. The ability of WO to improve cognitive efficacy in the TMT-induced neurodegenerative rats was investigated using a passive avoidance test, and the Morris water maze test, and using immunohistochemistry to detect components of the acetylcholinergic system, brain-derived neurotrophic factor (BDNF), and cAMP-response element-binding protein (CREB) expression. Rats injected with TMT showed impairments in learning and memory and daily administration of WO improved memory function, and reduced aggressive behavior. Administration of WO significantly alleviated the TMT-induced loss of cholinergic immunoreactivity and restored the hippocampal expression levels of BDNF and CREB proteins and their encoding mRNAs to normal levels. These findings suggest that WO might be useful as a new therapy for treatment of various neurodegenerative diseases.

• Journal of Gifted/Talented Education
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• v.19 no.3
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• pp.457-476
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• 2009

The research aimed to investigate characteristics of middle school students in a biology class as science gifted education in terms of self-regulated learning abilities, personality traits and learning preferences. The twenty subject in the study responded to questionnaires of a self-regulated learning ability instrument, a personality trait tool, and a learning preference survey in March, 2009. It was found that the research subjects showed higher levels of cognitive strategies, meta-cognition, and motivation than those students in a previous study(Jung et. al., 2004), while environment was opposite. The level of cognitive strategies was significantly correlated with meta-cognition(r=.610, p=.004) and motivation (r=.538, p=.014) and meta-cognition with environment(r=.717, p=.000). Those students who showed highest levels of self-regulated learning ability displayed various personality traits. One male student with the highest level of self-regulated learning ability showed a personality of hardworking, tender-minded, and conscientious traits and wanted to be a medical doctor. The female student with the second highest level of self-regulated learning ability presented a personality as creative, abstract and divergent thinker and she showed a strong aspiration to be a world-famous biologist with breakthrough contribution. The five students with highest levels of self-regulated learning ability showed a common preference in science learning: they dislike memory-oriented and theory-centered lecture with note-taking from teacher's writings on chalkboard; they prefer science learning with inquiry-oriented laboratory work, discussion among students as well as teachers. However, reasons to prefer discussion were diverse as one student wants to listen other students' opinions while the other student want to present his opinion to other students. The most favorable science teachers appeared to be who ask questions frequently, increase student interests, behave friendly with students, and is a active person. In conclusion, science teaching for the gifted should employ individualized teaching strategies appropriate for individual personality and preferred learning styles as well as meeting with individual interests in science themes.

• Laboraroty Animal Research
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• v.34 no.4
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• pp.317-328
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• 2018

Cognitive impairment responses are important research topics in the study of degenerative brain diseases as well as in understanding of human mental activities. To compare response to scopolamine (SPL)-induced cognitive impairment, we measured altered parameters for learning and memory ability, inflammatory response, oxidative stress, cholinergic dysfunction and neuronal cell damages, in Korl:ICR stock and two commercial breeder stocks (A:ICR and B:ICR) after relevant SPL exposure. In the water maze test, Korl:ICR showed no significant difference in SPL-induced learning and memory impairment compared to the two different ICRs, although escape latency was increased after SPL exposure. Although behavioral assessment using the manual avoidance test revealed reduced latency in all ICR mice after SPL treatment as compared to Vehicle, no differences were observed between the three ICR stocks. To determine cholinergic dysfunction induction by SPL exposure, activity of acetylcholinesterase (AChE) assessed in the three ICR stocks revealed no difference of acetylcholinesterase activity. Furthermore, low levels of superoxide dismutase (SOD) activity and high levels of inflammatory cytokines in SPL-treated group were maintained in all three ICR stocks, although some variations were observed between the SPL-treated groups. Neuronal cell damages induced by SPL showed similar response in all three ICR stocks, as assessed by terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assay, Nissl staining analysis and expression analyses of apoptosis-related proteins. Thus, the results of this study provide strong evidence that Korl:ICR is similar to the other two ICR. Stocks in response to learning and memory capacity.

• Herbal Formula Science
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• v.16 no.1
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• pp.131-145
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• 2008

With tablets and powder, decoction has been a widely-used method of medicine formula. However, for these formulas have unique bitter tastes and flavors of herbal component materials as it is, the compliance of herbal medicine is severly decreased especially for female and younger patients. Consequently, expected treatment effects can't be acquired completely. If loathsome tastes and flavors of decoction were effectively reduced while pharmacological activity were kept intact, the compliance could be promoted Chong-Myung-Tang has been widely prescribed for student patients with memory This study shows that Chong-Myung-Tang+chocolate have no difference from Chong-Myung-Tang in terms of pharmacological activity. Sensory difference with net chocolate was also surved. In order to observe the difference of Chong-Myung-Tang+chocolate and Chong-Myung-Tang, memory impairment was induced by intraventricular injection of $A{\beta}_{25-35}$ peptides on mice and Chong-Myung-Tang and Chong-Myung-Tang+chocolate were administered orally for 14 days. In water maze task, improvement of learning ability during acquisition period and significant increase of memory score during retention period resulted from the treatment of Chong-Myung-Tang and Chong-Myung-Tang+chocolate with respect to the $A{\beta}-injected$ control animals. Furthermore, the $A{\beta}_{25-35}$ toxicity on the hippocampus was assessed with immunohistochemistry (Bax, TUNEL), and differences in antioxidant activity was observed through TBARS and DPPH test. We employed sensory tests using chocolate flavor, herb flavor, and bitter taste & hardness as standards to show sensory differences with net chocolate. In this study, it is demonstrated that Chong-Myung-Tang+chocolate do not disturb the pharmacological activity of Chong-Myung-Tang, and have no sensory difference with net chocolate. Chong-Myung-Tang+chocolate can be used to enhance the compliance remarkably and thought of as an effective, functional formula to maximize expected treatment.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.11
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• pp.94-101
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• 2020

In the age of industry 4.0, artificial intelligence is being widely used to realize machinery condition monitoring. Due to their excellent performance and the ability to handle large volumes of data, machine learning techniques have been applied to realize the fault diagnosis of different equipment. In this study, we performed the failure mode effect analysis (FMEA) of an aluminum electrolytic capacitor by using deep learning and big data. Several tests were performed to identify the main failure mode of the aluminum electrolytic capacitor, and it was noted that the capacitance reduced significantly over time due to overheating. To reflect the capacitance degradation behavior over time, we employed the Vanilla long short-term memory (LSTM) neural network architecture. The LSTM neural network has been demonstrated to achieve excellent long-term predictions. The prediction results and metrics of the LSTM and Vanilla LSTM models were examined and compared. The Vanilla LSTM outperformed the conventional LSTM in terms of the computational resources and time required to predict the capacitance degradation.