• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.675-679
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• 2001

In this paper, we present a new competitive learning algorithm called Dynamic Competitive Learning (DCL). DCL is a supervised learning method that dynamically generates output neurons and initializes automatically the weight vectors from training patterns. It introduces a new parameter called LOG (Limit of Grade) to decide whether an output neuron is created or not. If the class of at least one among the LOG number of nearest output neurons is the same as the class of the present training pattern, then DCL adjusts the weight vector associated with the output neuron to learn the pattern. If the classes of all the nearest output neurons are different from the class of the training pattern, a new output neuron is created and the given training pattern is used to initialize the weight vector of the created neuron. The proposed method is significantly different from the previous competitive learning algorithms in the point that the selected neuron for learning is not limited only to the winner and the output neurons are dynamically generated during the learning process. In addition, the proposed algorithm has a small number of parameters, which are easy to be determined and applied to real-world problems. Experimental results for pattern recognition of remote sensing data and handwritten numeral data indicate the superiority of DCL in comparison to the conventional competitive learning methods.

• Molecules and Cells
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• v.46 no.11
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• pp.672-674
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• 2023

Schematic diagram of the interaction between the intestinal muscularis externa (MMΦ) macrophages and the enteric nervous system (ENS) neurons during different developmental periods. At the early postnatal stage, MMΦs play a critical role in ENS maturation and refinement through synaptic pruning and enteric neuron phagocytosis. In addition, during the adult stage, a specific MMΦ subset named neuron-associated (NA)-MMΦ, supports enteric neuronal survival and functions. Conversely, enteric neurons promote the phenotypic MMΦ changes by secreting transforming growth factor-β (TGFβ), transitioning them from a phagocytic phenotype in the early postnatal period to a neuroprotective and immune-surveillant phenotype in the young adult period. Disruptions in these interactions could lead to alterations in the enteric neuron numbers, ultimately resulting in reduced gut motility.

• Annual Conference of KIPS
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• 2022.11a
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• pp.37-39
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• 2022

KISTI(한국과학기술정보연구원)는 슈퍼컴퓨터 5호기 메인시스템인 Nurion과 보조시스템인 Neuron을 연구자들에게 서비스하고 있다. Neuron은 메인시스템인 Nurion이 Intel Knights Landing 프로세서가 장착된 클러스터로 구성됨에 따라 인공지능, 빅데이터에 관한 연구 인프라 수요를 충족시키기 위해 GPU를 장착한 이기종 클러스터로 구성되어 있다. Neuron은 연구자들에게 효율적으로 계산 자원을 배분하기 위해 SLURM 작업배치스케줄러의 공유노드 정책을 이용하여 한 개의 계산노드에서 다수 개의 작업이 수행될 수 있는 환경으로 서비스되고 있다. 본 논문에서는 공유노드 정책으로 운영 중인 클러스터 시스템에서 작업별로 GPU 사용 통계 데이터를 생성하는 기법을 소개한다.

• 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 Intelligence and Information Systems
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• v.11 no.2
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• pp.81-103
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• 2005

The Neuron structure in a nervous system consists of inhibitory neurons and excitory neurons. Both neurons are activated by agonistic neurons and inactivated by antagonist neurons. In this paper, we proposed a physiological fuzzy neural network by analyzing the physiological neuron structure in the nervous system. The proposed structure selectively activates the neurons which go through a state of excitement caused by agonistic neurons and also transmit the signal of these neurons to the output layers. The proposed physiological fuzzy neural networks based on the nervous system consists of a input player, and the hidden layer which classifies features of learning data, and output layer. The proposed fuzzy neural network is applied to recognize bronchial squamous cell carcinoma images and car plate images. The result of the experiments shows that the learning time, the convergence, and the recognition rate of the proposed physiological fuzzy neural networks outperform the conventional neural networks.

• The Journal of Korean Physical Therapy
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• v.19 no.1
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• pp.11-22
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• 2007

Purpose: The purpose of this study were to analysis the effect on change of spinal neuron excitability during gait training of hemiplegia patients by the functional electrical stimulation. Methods: Thirty six hemiplegia patients participated in this study. Stimulation conditions of FES were pulse rate 35pps, pulse width $250{\mu}s$, and on-time 0.3 second, treatment hour was 30 min. and treatment period was once a day for five days a week through six weeks. For functional evaluations before and after treatment, Modified Ashworth Scale (MAS), active range of motion (AROM), Hmax threshold, H/Mmax ratio were measured and the following conclusions were obtained. Results: Functional evaluation showed significant changes in experimental group as MAS(p<0.01), AROM(p<0.001), compared to control group. In spinal neuron excitability evaluation, change of Hmax threshold was significantly reduced in both non weight bearing (p<0.001) and bearing condition (p<0.05), H/Mmax ratio was significantly reduced in non weight bearing (p<0.05) and bearing condition (p<0.05). Conclusion: In conclusion, application of FES to hemiplegia patients in recovery stage during gait training improved mitigation of muscular spasticity, balance adjustment and moving ability and it was interpreted that it was caused by mitigation of muscular spasticity by the spinal neuron excitability.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.137-143
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• 2005

Autonomous mobile robot has an ability to navigate using both map in known environment and sensors for detecting obstacles in unknown environment. In general, autonomous mobile robot navigates by global path planning on the basis of already made map and local path planning on the basis of various kinds of sensors to avoid abrupt obstacles. This paper provides a global path planning method using self-organizing feature map which is a method among a number of neural network. The self-organizing feature map uses a randomized small valued initial weight vectors, selects the neuron whose weight vector best matches input as the winning neuron, and trains the weight vectors such that neurons within the activity bubble are move toward the input vector. On the other hand, the modified method in this research uses a predetermined initial weight vectors, gives the systematic input vector whose position best matches obstacles, and trains the weight vectors such that neurons within the activity bubble are move toward the input vector. According to simulation results one can conclude that the modified neural network is useful tool for the global path planning problem of a mobile robot.

• Clinical and Experimental Pediatrics
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• v.51 no.12
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• pp.1350-1354
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• 2008

Spinal muscular atrophy (SMA) is an autosomal recessive disease characterized by diffuse proximal and distal weakness due to deletion of the survival motor neuron (SMN) gene localized on chromosome 5 (5q11.2-13.3). SMA has been considered as a pure lower motor neuron disorder, and a definitive diagnosis can be established by molecular genetic testing. Here, we describe two patients with severe hypotonia and frequent aspirations at early infancy. Nerve conduction studies showed more extensive sensory involvement in these patients diagnosed to have SMA by genetic study than in classical cases of SMA. To the best of our knowledge, this is the first report of SMA Type 1 with sensory nerve involvement in Korea.

• BMB Reports
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• v.49 no.11
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• pp.587-589
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• 2016

The circadian clock system enables organisms to anticipate the rhythmic environmental changes and to manifest behavior and physiology at advantageous times of the day. Transcriptional/translational feedback loop (TTFL) is the basic feature of the eukaryotic circadian clock and is based on the rhythmic association of circadian transcriptional activator and repressor. In Drosophila, repression of dCLOCK/CYCLE (dCLK/CYC) mediated transcription by PERIOD (PER) is critical for inducing circadian rhythms of gene expression. Pacemaker neurons in the brain control specific circadian behaviors upon environmental timing cues such as light and temperature cycle. We show that amino acids 657-707 of dCLK are important for the transcriptional activation and the association with PER both in vitro and in vivo. Flies expressing dCLK lacking AA657-707 in $Clk^{out}$ genetic background, homologous to the mouse Clock allele where exon 19 region is deleted, display pacemaker-neuron-dependent perturbation of the molecular clockwork. The molecular rhythms in light-cycle-sensitive pacemaker neurons such as ventral lateral neurons ($LN_vs$) were significantly disrupted, but those in temperature-cycle-sensitive pacemaker neurons such as dorsal neurons (DNs) were robust. Our results suggest that the dCLK-controlled TTFL diversify in a pacemaker-neuron-dependent manner which may contribute to specific functions such as different sensitivities to entraining cues.

• Journal of the Korea Convergence Society
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• v.8 no.8
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• pp.225-230
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• 2017

The Sijo provides dynamic rated therapeutic activities in our life. This study aims to search for the literary therapeutic function secreted from the Sijo that ends with a noun. As a result, the noun used at the final sentence secretes a predicative function. This kind of Sijo functions as twelve sound steps, even though it is condensed of just eleven sound steps with one sound step omitted. This functional secretion of Sijo is therapeutic predicate concerned with encoding of literary therapy. Thus it become possible to activate the therapeutic encoding in Sijo or a language by uttering only noun, instead of the predicate. That's because the noun in the last sentence of Sijo permeated in the human body and is done subject, and neuron of the body becomes a predicate, so that the Sijo's subject and the neuron's predicate are fused into a sentence. During the course the human body seems to recognize that the neuron's nucleus analyzes the information of the noun and makes a new sentence. This recognition might also be regarded as a process of encoding that has therapeutic functions secreted from the human body.