• Journal of the Korean Society for Precision Engineering
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• v.23 no.3 s.180
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• pp.94-101
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• 2006

A global path planning method using self-organizing feature map which is a method among a number of neural network is presented. 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 moved toward the input vector On the other hand, the modified method in this research uses a predetermined initial weight vectors of 1-dimensional string and 2-dimensional mesh, gives the systematic input vector whose position best matches obstacles, and trains the weight vectors such that neurons within the activity bubble are moved 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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.1058-1062
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• 2003

This paper proposes a self-organizing fuzzy controller (SOFC) design technique applied to the vibration control of a dynamic system under irregular disturbance. In this controller, the fuzzy rules generate control signal continuously using the array of input and output pairs without using any special controller model. The generated rules are saved in the fuzzy rule matrix in real-time by self-organizing methods. This fuzzy logic control is demonstrated by simulation and shows the efficiency of the real-time self-organizing fuzzy controller in this system.

• Journal of the Korean Institute of Navigation
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• v.22 no.4
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• pp.21-29
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• 1998

The marine self-organizing VHF data link is a digital radio link with self-organizing ability, which exploits the STDMA algorithm and operates in marine VHF channels. It can support the applications of surveillance, situation awareness and communication. It is the core technology of the Universal AIS which is considered as a future surveillance system at sea by the IMO. In this paper, the operational principle of the marine self-organizing VHF data link is introduced. Simultaneously, a new access protocol is proposed to enhance the marine self-organizing VHF data link so as to support point-to-point communication. The point-to-point communication is one of the most important bases to establish dynamic internetworks among computers on the bridges in the future.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.5
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• pp.353-360
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• 2004

This paper considers reinforcement learning control with the self-organizing map. Reinforcement learning uses the observable states of objective system and signals from interaction of the system and environment as input data. For fast learning in neural network training, it is necessary to reduce learning data. In this paper, we use the self-organizing map to partition the observable states. Partitioning states reduces the number of learning data which is used for training neural networks. And neural dynamic programming design method is used for the controller. For evaluating the designed reinforcement learning controller, an inverted pendulum on the cart system is simulated. The designed controller is composed of serial connection of self-organizing map and two Multi-layer Feed-Forward Neural Networks.

• Journal of Korea Multimedia Society
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• v.3 no.4
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• pp.416-423
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• 2000

The existing self-organizing feature map of Kohonen has weakpoint that need too much input patterns in order to converse into the learning rate and equilibrium state when it trains. Making up for the current weak point, B.Bavarian suggested the method of that distributed the learning rate such as Gaussian function. However, this method has also a disadvantage which can not achieve the right self-organizing. In this paper, we proposed the method of improving the convergence speed and the convergence rate of self-organizing feature map converting the Gaussian function into dynamic approximate curve used in when trains the self-organizing feature map.

• Journal of Yeungnam Medical Science
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• v.25 no.2
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• pp.117-123
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• 2008

Dermatomyositis is characterized by progressive, symmetric, proximal muscle weakness and a nonsuppurative inflammatory myopathy of unknown etiology involving predominantly skeletal muscles. It is also characterized by typical skin lesions. Interstitial lung disease has a poor prognosis when it is associated with dermatomyositis. Organizing pneumonia is a disease in which granulation tissue fills the lumina of terminal and respiratory bronchioles and extends into the distal airspaces. The cryptogenic nature of the process is appreciated in that organizing pneumonia patterns of injury can be seen in secondary forms of the disease (secondary organizing pneumonia). Organizing pneumonia has been reported to occur in 5~10% in dermatomyositis-polymyositis patients. Anti-histidyl tRNA synthetase antibody (anti-Jo-1) is a predictive disease marker that is reported to occur in up to 70% of patients. We describe a 49-year-old male dermatomyositis patient who presented with organizing pneumonia and was found to have negative anti-Jo-1 antibody.

• Tuberculosis and Respiratory Diseases
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• v.77 no.6
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• pp.262-265
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• 2014

The combination chemotherapy of irinotecan with 5-fluorouracil and leucovorin (FOLFIRI regimen) was recently proven to be beneficial in patients with advanced colorectal cancer. Pulmonary toxicity is very rare in adverse effects of irinotecan. No case of organizing pneumonia (also known as bronchiolitis obliterans organizing pneumonia) associated with FOLFIRI chemotherapy has been reported. We experienced a case of a 62-year-old man who presented persistent dry cough and progressive dyspnea after receiving chemotherapy with FOLFIRI regimen. After surgical lung biopsy, the patient was diagnosed with FOLFIRI chemotherapy-induced organizing pneumonia which was successfully treated with steroid therapy.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.170-177
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• 2003

Gene expression data are the quantitative measurements of expression levels and ratios of numberous genes in different situations based on microarray image analysis results. The process to draw meaningful information related to genomic diseases and various biological activities from gene expression data is known as gene expression data analysis. In this paper, we present a hierarchical clustering method of gene expression data based on self organizing map which can analyze the clustering result of gene expression data more efficiently. Using our proposed method, we could eliminate the uncertainty of cluster boundary which is the inherited disadvantage of self organizing map and use the visualization function of hierarchical clustering. And, we could process massive data using fast processing speed of self organizing map and interpret the clustering result of self organizing map more efficiently and user-friendly. To verify the efficiency of our proposed algorithm, we performed tests with following 3 data sets, animal feature data set, yeast gene expression data and leukemia gene expression data set. The result demonstrated the feasibility and utility of the proposed clustering algorithm.

• Journal of Microbiology and Biotechnology
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• v.11 no.5
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• pp.739-748
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• 2001

A self-organizing fuzzy logic controller using a genetic algorithm is described, which controlled the glucose concentration for the enhancement of flavonoid production in a fed-batch cultivation of Scutellaria baicalensis G. plant cells. The substrate feeding strategy in a fed-batch culture was to increase the flavonoid production by using the proposed kinetic model. For the two-stage culture, the substrate feeding strategy consisted of a first period with 28 g/I of glucose to promote cell growth, followed by a second period with 5 g/I of glucose to promote flavonoid production. A simple fuzzy logic controller and the self-organizing fuzzy logic controller using a genetic algorithm was constructed to control the glucose concentration in a fed-batch culture. The designed fuzzy logic controllers were applied to maintain the glucose concentration at given set-points of the two-stage culture in fed-batch cultivation. The experimental results showed that the self-organizing fuzzy logic controller improved the controller\`s performance, compared with that of the simple fuzzy logic controller. The specific production yield and productivity of flavonoids in the two-stage culture were higher than those in the batch culture.

• 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.