• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.791-799
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• 2013

This study to evaluate the spinal motor neuron and electroencephalogram effects of applying different kinesio taping method therapy in normal people. The study was performed on 16 healthy adults. We divide two group; group I(n=8); Tape along muscle, group II(n=8); Tape across muscle. Two different method taping were applied to gastrocnemius in two weeks. Spinal motor neuron measurement to evoke H-reflex, the posterior tibial nerve was stimulated. Electroencephalogram measurement for ${\beta}$-SMR, attached to active electrode C3, Cz, C4. The H-reflex, ${\beta}$-SMR results were measured before, immediately, one week later and two week later after the apply taping. The results of this study, spinal motor neuron change of group I were decreased ${\alpha}$-motor neuron and the duration time longer than group II(p<.05). Electroencephalogram change of group I were increased ${\beta}$-SMR and the duration time longer than group II(p<.05). Thus, we knew the taping along muscle was ${\beta}$-SMR brain wave more active and reduces the activity of spinal motor neuron.

• The Journal of the Korea Contents Association
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• v.9 no.9
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• pp.278-286
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• 2009

The aims of this study were to determined whether excitability of the $\alpha$-motor neuron is modulated by stretching and this changes were associated with flexibility of the muscle. In this study, $\alpha$-motor neuron excitability was measured by using the Hmax/Mmax ratio of the gastrocnemius H-reflex, and muscle flexibility was measured with the range of motion of the ankle dorsiflexion. The gastrocnemii of 10 healthy volunteers were stretched for 4 minutes(2 minutes stretching, 1 minute rest, and 2 minutes stretching) in each session by manual force. The Hmax/Mmax ratio of the H-reflex, as well as the range of motion of the ankle dosiflexion was measured through four different conditions: before stretching, as soon as after $1^{st}$ stretching, as soon as after $2^{nd}$ stretching and at 48 hours after $2^{nd}$ stretching. Excitability of the $\alpha$-motor neuron was decreased significantly after $1^{st}$ and $2^{nd}$ stretching(p<0.05). Furthermore, the range of the dorsiflexion was increased significantly after $1^{st}$ and $2^{nd}$ stretching(p<0.05). However, the excitability of the $\alpha$-motor neuron and range of the dorsiflexion at 48 hours after $2^{nd}$ stretching were not different from those of before stretching. These results suggest that reduced $\alpha$-motor neuron excitability of the gastrocnemius and increased flexibility of the ankle dorsiflexion would be followed by activation of the type III mechanoreceptor which around the ankle joint and the Golgi tendon organ in the gastrocnemius.

• Smart Structures and Systems
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• v.29 no.1
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• pp.1-16
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• 2022

Despite recent breakthroughs in deep learning and computer vision fields, the pixel-wise identification of tiny objects in high-resolution images with complex disturbances remains challenging. This study proposes a modified U-net for tiny crack segmentation in real-world steel-box-girder bridges. The modified U-net adopts the common U-net framework and a novel Self-Attention-Self-Adaption (SASA) neuron as the fundamental computing element. The Self-Attention module applies softmax and gate operations to obtain the attention vector. It enables the neuron to focus on the most significant receptive fields when processing large-scale feature maps. The Self-Adaption module consists of a multiplayer perceptron subnet and achieves deeper feature extraction inside a single neuron. For data augmentation, a grid-based crack random elastic deformation (CRED) algorithm is designed to enrich the diversities and irregular shapes of distributed cracks. Grid-based uniform control nodes are first set on both input images and binary labels, random offsets are then employed on these control nodes, and bilinear interpolation is performed for the rest pixels. The proposed SASA neuron and CRED algorithm are simultaneously deployed to train the modified U-net. 200 raw images with a high resolution of 4928 × 3264 are collected, 160 for training and the rest 40 for the test. 512 × 512 patches are generated from the original images by a sliding window with an overlap of 256 as inputs. Results show that the average IoU between the recognized and ground-truth cracks reaches 0.409, which is 29.8% higher than the regular U-net. A five-fold cross-validation study is performed to verify that the proposed method is robust to different training and test images. Ablation experiments further demonstrate the effectiveness of the proposed SASA neuron and CRED algorithm. Promotions of the average IoU individually utilizing the SASA and CRED module add up to the final promotion of the full model, indicating that the SASA and CRED modules contribute to the different stages of model and data in the training process.

• International journal of advanced smart convergence
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• v.8 no.4
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• pp.104-112
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• 2019

This study proposed a robust detection algorithm. It detects face more stably with respect to changes in light and rotation forthe identification of a face shape. The proposed algorithm uses face shape asinput information in a single camera environment and divides only face area through preprocessing process. However, it is not easy to accurately recognize the face area that is sensitive to lighting changes and has a large degree of freedom, and the error range is large. In this paper, we separated the background and face area using the brightness difference of the two images to increase the recognition rate. The brightness difference between the two images means the difference between the images taken under the bright light and the images taken under the dark light. After separating only the face region, the face shape is recognized by using the self-organization feature map (SOFM) algorithm. SOFM first selects the first top neuron through the learning process. Second, the highest neuron is renewed by competing again between the highest neuron and neighboring neurons through the competition process. Third, the final top neuron is selected by repeating the learning process and the competition process. In addition, the competition will go through a three-step learning process to ensure that the top neurons are updated well among neurons. By using these SOFM neural network algorithms, we intend to implement a stable and robust real-time face shape recognition system in face shape recognition.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.136-141
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• 2007

This paper introduces an artificial neuron which is a nano composite continuous sensor. The continuous nano sensor is fabricated as a thin and narrow polymer film sensor that is made of carbon nanotubes composites with a PMMA or a silicone matrix. The sensor can be embedded onto a structure like a neuron in a human body and it can detect deteriorations of the structure. The electrochemical impedance and dynamic strain response of the neuron change due to deterioration of the structure where the sensor is located. A network of the long nano sensor can form a structural neural system to provide large area coverage and an assurance of the operational health of a structure without the need for actuators and complex wave propagation analyses that are used with other methods. The artificial neuron is expected to effectively detect damage in large complex structures including composite helicopter blades and composite aircraft and vehicles.

• Annals of Clinical Neurophysiology
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• v.11 no.2
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• pp.74-77
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• 2009

We report a 23-year-old woman with adult Sandhoff disease, who presented with motor neuron disease phenotype. The patient had experienced progressive motor weakness in four extremities since 1 year prior to admission. Electrophysiological study revealed wide-spread denervation potentials, and the assay of total hexosaminidase involving A and B activities showed decreased levels of these activities, which was consistent with Sandoff disease. This is the first Korean case of adult Sanhoff disease presented as a motor neuron disease phenotype.

• Journal of Physiology & Pathology in Korean Medicine
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• v.16 no.3
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• pp.563-566
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• 2002

To evaluate the effect of Jingansikpung-tang(JST) water extract on cultured mouse spinal sensory neuron which was inhibited by glucose oxidase(GO)-induced cytotoxicity, MTT and LDH activity assay were carried out after the cultured mouse spinal sensory neuron were pre-incubated with various concentrations of JST extract for 3 hours prior to exposure of GO. The results obtained were as follows: GO, a oxygen radical, decreased the survival rate of the cultured mouse spinal sensory neuron cells on MTT assay. JST water extract have efficacy of decreasing LDH activity increasing by GO in cultured mouse spinal sensory neuron. From above the results, it is concluded that JST water extract has marked efficacy as a treatment for the damages caused in the GO-mediated oxidative process.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.3
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• pp.201-210
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• 2002

This paper describes a 3.3 (V) low power 4 digit CMOS quaternary to analog converter (QAC) designed with a neuron MOS($\upsilon$MOS) down literal circuit block and cascode current mirror source block. The neuron MOS down literal architecture allows the designed QAC to accept not only 4 level voltage inputs, but also a high speed sampling rate quaternary voltage source LSB. Fast settling time and low power consumption of the QAC are achieved by utilizing the proposed architecture. The simulation results of the designed 4 digit QAC show a sampling rate of 6(MHz) and a power dissipation of 24.5 (mW) with a single power supply of 3.3 (V) for a CMOS 0.35${\mu}{\textrm}{m}$ n-well technology.

• Journal of IKEEE
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• v.7 no.2 s.13
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• pp.135-143
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• 2003

This paper describes the design techniques of the data converters for Multiple-Valued Logic(MVL). A 3.3V low power 4 digit CMOS analog to quaternary converter (AQC) and quaternary to analog converter (QAC) mainly designed with the neuron MOS down literal circuit block has been introduced. The neuron MOS down literal architecture allows the designed AQC and QAC to accept analog and 4 level voltage inputs, and enables the proposed circuits to have the multi-threshold properity. Low power consumption of the AQC and QAC are achieved by utilizing the proposed architecture.

• PNF and Movement
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• v.13 no.4
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• pp.175-180
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• 2015

Purpose: This study aimed to examine the effects of mirror-neuron-system-based action observation physical training on improvements in upper extremity functions and daily living activities in chronic stroke patients. Methods: Ten chronic stroke patients were randomly selected. As a therapeutic intervention, along with conventional occupational therapy, the patients engaged in action observation physical training through repeated imitation practices after they viewed a video. The therapeutic intervention was implemented for 20 minutes, three times each week for eight weeks. A Manual Function Test (MFT) was conducted to compare upper extremity functions before and after the therapeutic intervention, and the Modified Barthel Index (MBI) was used to compare the ability to perform daily living activities. Results: Significant improvements in upper extremity motor functions and the ability to perform daily living activities were shown after the intervention. The subjects' left upper extremity motor functions and ability to perform daily living activities showed significant improvement after the intervention. Conclusion: The study's results indicate that action observation physical training based on the mirror neuron system improves chronic stroke patients' upper extremity motor functions and their ability to perform daily living activities. Therefore, action observation training has positive effects on the functional recovery of chronic stroke patients.