• The Journal of the Acoustical Society of Korea
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• v.22 no.2E
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• pp.49-55
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• 2003

The modified neural net pattern recognition equations were attempted to apply to speech recognition. The proposed method has a dynamic process of self-organization that has been proved to be successful in recognizing a depth perception in stereoscopic vision. This study has shown that the process has also been useful in recognizing human speech. In the processing, input vocal signals are first compared with standard models to measure similarities that are then given to a process of self-organization in neural net equations. The competitive and cooperative processes are conducted among neighboring input similarities, so that only one winner neuron is finally detected. In a comparative study, it showed that the proposed neural networks outperformed the conventional HMM speech recognizer under the same conditions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.995-998
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• 2013

Aerial imaging is one of the most common and versatile ways of obtaining information from the Earth surface. In this paper, we present an approach by SOM(Self Organization Map) algorithm with 2 phase learning to be applied successfully to aerial images clustering due to its signal-to-noise independency. A comparison with other classical method, such as K-means and traditional SOM, of real-world areal image clustering demonstrates the efficacy of our approach.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.1035-1037
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• 2009

Common to use fixed-node sensor network and wireless sensor networks, unlike the recent move of the node happens frequently. These wireless sensor networks by taking into account the mobility of sensor nodes dynamically self-configurable routing protocol is required. In this paper, a fixed-node configuration and energy efficiency in the self-LEACH protocol is based on the useful movement of the nodes of the cluster is dynamically self-configuring routing protocols offer M-LEACH.

• Journal of Communications and Networks
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• v.11 no.1
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• pp.57-71
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• 2009

Networking together hundreds or thousands of cheap sensor nodes allows users to accurately monitor a remote environment by intelligently combining the data from the individual nodes. As sensor nodes are typically battery operated, it is important to efficiently use the limited energy of the nodes to extend the lifetime of the wireless sensor network (WSN). One of the fundamental issues in WSNs is the coverage problem. In this paper, the border coverage problem in WSNs is rigorously analyzed. Most existing results related to the coverage problem in wireless sensor networks focused on planar networks; however, three dimensional (3D) modeling of the sensor network would reflect more accurately real-life situations. Unlike previous works in this area, we provide distributed algorithms that allow the selection and activation of an optimal border cover for both 2D and 3D regions of interest. We also provide self-healing algorithms as an optimization to our border coverage algorithms which allow the sensor network to adaptively reconfigure and repair itself in order to improve its own performance. Border coverage is crucial for optimizing sensor placement for intrusion detection and a number of other practical applications.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.4
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• pp.278-289
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• 2013

Up-to-date market dynamics and intense competition have forced a production system to be more widely distributed and decentralized than ever, and the production system itself can be regarded as a collaborative network of autonomous production resources in which the responsibility of decision making is also decentralized into individual autonomous entities. The conventional resource management models, however, are not suitable for the distributed and decentralized environment because of their centralized nature. In this paper, an agent-based resource management model is proposed. The proposed model applies employment relation-driven fractal organization (FrOrg) into organizational model for distributed production resources and presents a resource management framework based on employment contracts. The fractal organization is a structured association in which a self-similar pattern recursively appears, and employment relations between production resources are recursively constructed throughout the entire production system.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.23 no.1
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• pp.85-95
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• 2015

A responsibility of superior management in an airline has become enormous due to rapid increase of airline's organization and its network. Even though a leadership of superior management is believed to be an important factor, it is almost impossible for management to be responsible for all the areas of an airline organization. This is why leadership should be go down to working level people. Self-leadership means that working level people possess leadership, delegated by their superior persons, and improve their work environment with the leadership as well as related right and responsibility. This paper has tried to find out the components of self-leadership perceived by foreign cabin crews and analyzed the impact of self leadership into airline's organizational effectiveness. Based on empirical research results, this paper would suggest administrative and operational implications of managing foreign cabin crews in K-airline. It was found out foreign cabin crews perceive that self reward and self evaluation have a positive impact on self observation factor. The self observation factor has a significant effect on self goal. The self goal is analyzed as a major factor which results in organizational effectiveness.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1015-1018
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• 1999

This paper describes a vector quantization for speech signal coding using neural networks. We processed speech signal using LPC method that extracts speech signal feature, and speech signal feature is quantized using competitive neural network kohonen self-organization feature map.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.4
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• pp.97-109
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• 2000

This work proposes a neural network approach to solve vehicle routing problems which have diverse application areas such as vehicle routing and robot programming. In solving these problems, classical mathematical approaches have many difficulties. In particular, it is almost impossible to implement a real-time vehicle routing with multiple vehicles. Recently, many researchers proposed methods to overcome the limitation by adopting heuristic algorithms, genetic algorithms, neural network techniques and others. The most basic model for path planning is the Travelling Salesman Problem(TSP) for a minimum distance path. We extend this for a problem with dynamic upcoming of new positions with multiple vehicles. In this paper, we propose an algorithm based on SOM(Self-Organization Map) to obtain a sub-optimal solution for a real-time vehicle routing problem. We develope a model of a generalized multiple TSP and suggest and efficient solving procedure.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.188-191
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• 2003

In this paper, we proposed data generalization and data cube mechanism for efficient data mining in distribute environment. We also proposed active Self Organization Map applying traditional Self Organization Map of Neural network for searching the most Informative data created from data cube after the generalization procedure and designed the system architecture for that.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.932-945
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• 2018

Everything in the world is becoming connected and interactive due to the Internet. The future of interactive smart environments such as smart cities, smart industries, or smart farms demand high network bandwidth, high network flexibility, and self-organization systems without costly hardware upgrades, and they provide a sustainable, scalable, and replicable smart environment backbone infrastructure. This paper presents a new Hybrid Software-Defined architecture for integrating Internet-of-Things technologies that are essential technologies for smart environments. It combines a software-defined networking infrastructure and a real-time distributed network framework with an advanced optimization to enable self-configuration, self-management, and self-adaption for providing seamless communication and efficiently managing a vast number of smart heterogeneous devices.