• Journal of KIISE:Information Networking
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• v.35 no.2
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• pp.139-148
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• 2008

Many types of sensor data exhibit strong correlation in both space and time. Suppression, both temporal and spatial, provides opportunities for reducing the energy cost of sensor data collection. Unfortunately, existing clustering algorithms are difficult to utilize the spatial or temporal opportunities, because they just organize clusters based on the distribution of sensor nodes or the network topology but not correlation of sensor data. In this paper, we propose a novel clustering algorithm with suppression techniques. To guarantee independent communication among clusters, we allocate multiple channels based on sensor data. Also, we propose a spatio-temporal suppression technique to reduce the network traffic. In order to show the superiority of our clustering algorithm, we compare it with the existing suppression algorithms in terms of the lifetime of the sensor network and the site of data which have been collected in the base-station. As a result, our experimental results show that the size of data was reduced by $4{\sim}40%$, and whole network lifetime was prolonged by $20{\sim}30%$.

• Journal of the Economic Geographical Society of Korea
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• v.9 no.3
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• pp.273-296
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• 2006

The purpose of this paper is to investigate the formation and characteristics of Gwangju photonics agglomeration as a new agglomeration with a new industry. Data used in this study are locally investigatedfirm related data and the result of questionnaire surveys. Major findings are as follows. First, in the viewpoint of policy, national government suggested the whole policy frameworks and financial support for the strategic industrial development. Regional government picked up and fostered the strategic industry. The initial support of the national government and role of regional government triggered the initial development of the agglomeration. Second, in the spatial perspective, Gwangju photonics agglomeration is based on the externalities of knowledge and technology as well as the input-output network within value chains of production. There is a possibility that Gwangju photonics agglomeration will be developed as an innovation cluster of knowledge-based economy in the future beyond a mere production base of photonics.

• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.587-592
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• 2003

Many real world control problems have continuous states and actions. When the state space is continuous, the reinforcement learning problems involve very large state space and suffer from memory and time for learning all individual state-action values. These problems need function approximators that reason action about new state from previously experienced states. We introduce Fuzzy Q-Map that is a function approximators for 1 - step Q-learning and is based on fuzzy clustering. Fuzzy Q-Map groups similar states and chooses an action and refers Q value according to membership degree. The centroid and Q value of winner cluster is updated using membership degree and TD(Temporal Difference) error. We applied Fuzzy Q-Map to the mountain car problem and acquired accelerated learning speed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.12
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• pp.2800-2807
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• 2012

An ad-hoc wireless network provides self-organizing data networking while they are routing of packets among themselves. Typically multi-hop and control packets overhead affects the change of route of transmission. There are numerous routing protocols have been developed for ad hoc wireless networks as the size of the network scale. Hence the scalable routing protocol would be needed for energy efficient various network routing environment conditions. The number of depth or layer of hierarchical clustering nodes are analyzed the different clustering structure with topology in this paper. To estimate the energy efficient number of cluster layer and energy dissipation are studied based on distributed homogeneous spatial Poisson process with context-awareness nodes condition. The simulation results show that CACHE-R could be conserved the energy of node under the setting the optimal layer given parameters.

• Journal of the Korean Geographical Society
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• v.48 no.5
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• pp.629-650
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• 2013

This study reviews geographical research trends on 'New industrial agglomeration' in Korea and recommends research issues for further studies. Recent studies on industrial agglomeration region have typically concentrated on empirical case studies from new 'perspectives'. As a result, the establishment and theorizing of frameworks for analysis on industrial agglomeration have been given too little attention. To solve this problem research should be conducted to develop frameworks for analysis integrating noneconomic factors and existing economic factors, a strategy emphasized in new industrial agglomeration theory. By doing so, research investigating viability mechanism and generalization will be invigorated. Meanwhile, research focused excessively on social and cultural conditions of region-related networks between actors in economic space at specific scales should be excluded. In addition, academic research on vitalizing industrial agglomeration region, such as cluster policy, should be strengthened. In order to conduct these research objectives effectively, it is necessary to vitalize overall understanding among researchers of industrial agglomeration and provide a place for collaborative learning.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.3
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• pp.76-82
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• 2010

In this paper, we develop Linguistic Model (LM) based on information granules as a systematic approach to generating fuzzy if-then rules from a given input-output data. The LM introduced by Pedrycz is performed by fuzzy information granulation obtained from Context-based Fuzzy Clustering(CFC). This clustering estimates clusters by preserving the homogeneity of the clustered patterns associated with the input and output data. Although the effectiveness of LM has been demonstrated in the previous works, it needs to improve in the sense of performance. Therefore, we focus on the automatic generation of linguistic contexts, addition of bias term, and the transformed form of consequent parameter to improve both approximation and generalization capability of the conventional LM. The experimental results revealed that the improved LM yielded a better performance in comparison with LM and the conventional works for automobile MPG(miles per gallon) predication and Boston housing data.

• Journal of Digital Contents Society
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• v.18 no.5
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• pp.811-820
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• 2017

For content-based audio retrieval which is one of main functions in audio service, the techniques for extracting fingerprints from the audio source, storing and indexing them in a database are widely used. However, if the fingerprints of new audio sources are continually inserted into the database, there is a problem that space efficiency as well as audio retrieval performance are gradually deteriorated. Therefore, there is a need for techniques to support efficient expansion of audio database without periodic reorganization of the database that would increase the system operation cost. In this paper, we design a content-based audio retrieval system that solves this problem by using MapReduce and NoSQL database in a cluster computing environment based on the Shazam's fingerprinting algorithm, and evaluate its performance through a detailed set of experiments using real world audio data.

• Korean Journal of Crystallography
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• v.9 no.1
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• pp.48-52
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• 1998

The new Nd3Ba5Co4O15 phase was synthesized with Nd2O3, BaCO3, and Co3O4 by solid state reaction at 1200℃ with intermittent grinding. The crystal structure of Nd3Ba5Co4O15 has been refined on X-ray diffraction powder data by means of Rietveld method. The starting model was based on the Nd3.43Ba4.42Co2.23Al1.77O15 structure. The crystal system was hexagonal, space group P63mc(186), a=11.629(3) Å, c=6.842(2) Å. Final R values were Rwp=0.097 and Rp=0.068. The structure consists of clusters of CoVICoIV3O15 in which a CoVI octahedron shares corners with 3CoIV tetrahedra.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.89-97
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• 2011

In semantic web information system like ontology that access distributed information from network, efficient query processing requires an advanced caching mechanism to reduce the query response time. P2P network system have become an important infra structure in web environment. In P2P network system, when the query is initiated, reducing the demand of data transformation to source peer is important aspect of efficient query processing. Caching of query and query result takes a particular advantage by adding or removing a query term. Many of the answers may already be cached and can be delivered to the user right away. In web environment, semantic caching method has been proposed which manages the cache as a collection of semantic regions. In this paper, we propose the semantic caching technique in cluster environment of peers. Especially, using schema data filtering technique and schema similarity cache replacement method, we enhanced the query processing efficiency.

• The KIPS Transactions:PartD
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• v.11D no.4
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• pp.823-834
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• 2004

In this research, the similarity search algorithms are provided for large video data streams. A video stream that consists of a number of frames can be expressed by a sequence in the multidimensional data space, by representing each frame with a multidimensional vector By analyzing various characteristics of the sequence, it is partitioned into multiple video segments and clusters which are represented by hyper-rectangles. Using the hyper-rectangles of video segments and clusters, similarity functions between two video streams are defined, and two similarity search algorithms are proposed based on the similarity functions algorithms by hyper-rectangles and by representative frames. The former is an algorithm that guarantees the correctness while the latter focuses on the efficiency with a slight sacrifice of the correctness Experiments on different types of video streams and synthetically generated stream data show the strength of our proposed algorithms.