• Journal of Physiology & Pathology in Korean Medicine
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• v.16 no.5
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• pp.976-988
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• 2002

The aim of this study was to examine the memory and attention enhancement effect of YMG-1 and YMG-2, which are modified herbal extracts from Yukmijihwang-tang (YMJ). YMJ, composing six herbal medicine, has been used for restoring the normal functions of the body to consolidate the constitution, nourishing and invigorating the kidney functions for hundreds years in Asian countries. A series of studies reported that YMJ and its components enhance memory retention, protects neuronal cell from reactive oxygen attack and boost immune activities. Recently the microarray analysis suggested that YMG-1 protects neurodegeneration through modulating various neuron specific genes. A total of 55 subjects were divided into three groups according to the treatment of YMG-1 (n=20), YMG-2 (n=20) and control (C; n=15) groups. Before treatments, all of subjects were subjected to the assessments on neuropsychological tests of K-WAIS test, Rey-Kim memory test, and psychophysiological test of Event-Related Potential (ERP) during auditory oddball task and repeated word recognition task. They were repeatedly assessed with the same methods after drug treatment for 6 weeks. Although no significant effect of drug was found in Rey-Kim memory test, a significant interaction (P = .010, P < 0.05) between YMG-2 and C groups was identified in the scores digit span and block design, which are the subscales of K-WAIS. The very similar but marginal interaction (P = .064) between YMG-1 and C groups was found too. In ERP analysis, only YMG-1 group showed decreasing tendency of P300 latency during oddball task while the others tended to increase, and it caused significant interaction between session and group (p= .004). This result implies the enhancement of cognitive function in due to consideration of relationship between P300 latency and the speed of information processing. However, no evidence which could demonstrate the significant drug effect was found in neither amplitude or latency. These results come together suggest that YMG-1, 2 may enhance the attention, resulting in enhancement of memory processing. For elucidating detailed mechanism of YMG on learning and memory, the further studies are necessary.

• Journal of the korean academy of Pediatric Dentistry
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• v.25 no.4
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• pp.837-842
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• 1998

Rett syndrome is a progressive neurological disorder that occurs exclusively in females. The syndrome is characterized by regression of language, motor development, and stereotypic hand movement. Autistic behavior, breathing irregularities, gait dyspraxia, scoliosis, and seizure are also accompanied. The cause of Rett syndrome is unknown, however, it is believed that the X-chromosome might playa significant role in the development of the syndrome. Patients with this syndrome have unusual oral and/or digital habits such as abnormal chewing pattern, bruxism, hypersalivation, micrognathia, high vaulted palate, tongue protrusion with lower posture of tongue, hand biting, digit-hand sucking. Dentists who are aware of distinct manifestations of Rett syndrome will be able to aid in early diagnosis and treatment of the syndrome. Prior to dental treatment for a patient with the Rett syndrome under sedation or general anesthesia, one should assess the degree of hypersalivation, apnea, severity of autism, expected life span. Early recognition of the syndrome and also dental treatment with established strict preventive guidelines for patients with the Rett syndrome may obviate the necessity of sedation or general anesthesia. Two cases with the Rett syndome were reported. Both patients had most of the above mentioned typical manifestations of the syndrome. Dental treatment for the case 1(8-year-old) including caries control, stainless steel crown, sealant application was performed under general anesthesia. The case 2 could not be undergone the dental treatment due to poor general conditions.

• Journal of the Korea Society of Computer and Information
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• v.29 no.9
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• pp.1-7
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• 2024

In this paper, we proposes a Convolutional Neural Networks(CNN) equipped with Batch Normalization(BN) for handwritten digit recognition training the MNIST dataset. Aiming to surpass the performance of LeNet-5 by LeCun et al., a 6-layer neural network was designed. The proposed model processes 28×28 pixel images through convolution, Max Pooling, and Fully connected layers, with the batch normalization to improve learning stability and performance. The experiment utilized 60,000 training images and 10,000 test images, applying the Momentum optimization algorithm. The model configuration used 30 filters with a 5×5 filter size, padding 0, stride 1, and ReLU as activation function. The training process was set with a mini-batch size of 100, 20 epochs in total, and a learning rate of 0.1. As a result, the proposed model achieved a test accuracy of 99.22%, surpassing LeNet-5's 99.05%, and recorded an F1-score of 0.9919, demonstrating the model's performance. Moreover, the 6-layer model proposed in this paper emphasizes model efficiency with a simpler structure compared to LeCun et al.'s LeNet-5 (7-layer model) and the model proposed by Ji, Chun and Kim (10-layer model). The results of this study show potential for application in real industrial applications such as AI vision inspection systems. It is expected to be effectively applied in smart factories, particularly in determining the defective status of parts.