• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.1
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• pp.88-93
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• 2005

Web usage mining is a research field for searching potentially useful and valuable information from web log file. Web log file is a simple list of pages that users refer. Therefore, it is not easy to analyze user's current interest field from web log file. This paper presents web usage mining method for finding users' current interest based on fuzzy categories. We consider not only how many times a user visits pages but also when he visits. We describe a user's current interest with a fuzzy interest degree to categories. Based on fuzzy categories and fuzzy interest degrees, we also propose a method to cluster users according to their interests for user modeling. For user clustering, we define a category vector space. Experiments show that our method properly reflects the time factor of users' web visiting as well as the users' visit number.

• Proceedings of the IEEK Conference
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• 2002.06b
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• pp.361-364
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• 2002

In this paper, we consider the problem of CLB based CPLD technology mapping for power minimization in combinational circuit. The problem has been previously proved to be NP-hard, and hence we present an efficient heuristic algorithm for it. The main idea of our algorithm is to exploit the "cut enumeration" and "feasible cluster" technique to generate possible mapping solutions for the sub-circuit rooted at each node. However, for the consideration of both run time and memory space, only a fixed-number of solutions are selected and stored by our algorithm. To facilitate the selection process, a method that correctly calculates the estimated power consumption for each mapped sub-circuit is developed. The experimental results show that our approach is shown a decrease of 30.5% compared with DDMAP and that of 15.63% for TEMPLA in the Power consumption.

• ETRI Journal
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• v.42 no.3
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• pp.341-350
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• 2020

In a wireless sensor network (WSN), the data transmission technique based on the cooperative multiple-input multiple-output (CMIMO) scheme reduces the energy consumption of sensor nodes quite effectively by utilizing the space-time block coding scheme. However, in networks with high node density, the scheme is ineffective due to the high degree of correlated data. Therefore, to enhance the energy efficiency in high node density WSNs, we implemented the distributed source coding (DSC) with the virtual multiple-input multiple-output (MIMO) data transmission technique in the WSNs. The DSC-MIMO first compresses redundant source data using the DSC and then sends it to a virtual MIMO link. The results reveal that, in the DSC-MIMO scheme, energy consumption is lower than that in the CMIMO technique; it is also lower in the DSC single-input single-output (SISO) scheme, compared to that in the SISO technique at various code rates, compression rates, and training overhead factors. The results also indicate that the energy consumption per bit is directly proportional to the velocity and training overhead factor in all the energy saving schemes.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.496-499
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• 1999

This paper describes a medular neural network(MNN) for a vision system which tracks a given object using a sequence of images from a camera unit. The MNN is used to precisely recognize the given robot endeffector and to minize the processing time. Since the robot endeffector can be viewed in many different shapes in 3-D space, a MNN structure, which contains a set of feedforwared neural networks, co be more attractive in recognizing the given object. Each single neural network learns the endeffector with a cluster of training patterns. The training patterns for a neural network share the similar charateristics so that they can be easily trained. The trained MNN is less sensitive to noise and it shows the better performance in recognizing the endeffector. The recognition rate of MNN is enhanced by 14% over the single neural network. A vision system with the MNN can precisely recognize the endeffector and place it at the center of a display for a remote operator.

• Speech Sciences
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• v.15 no.4
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• pp.43-60
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• 2008

Instrumental studies (e.g., aerodynamic, EPG, and EMMA) have shown that the first of two stops in sequence can be articulatorily reduced in time and space sometimes; either gradient or categorical. The current EMMA study aims to examine possible factors_linguistic (e.g., speech rate, word boundary, and prosodic boundary) and paralinguistic (e.g., natural context and repetition)_to induce gradient reduction of $C_1$ in /pk/ cluster sequences. EMMA data are collected from five Seoul-Korean speakers. The results show that gradient reduction of lip aperture seldom occurs, being quite restricted both in speaker frequency and in token frequency. The results also suggest that the place assimilation is not a lexical process, implying that speakers have not fully developed this process to be phonologized in the abstract level.

• Genomics & Informatics
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• v.9 no.2
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• pp.89-91
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• 2011

DNA chips are becoming increasingly popular as a convenient way to perform vast amounts of experiments related to genes on a single chip. And the importance of analyzing the data that is provided by such DNA chips is becoming significant. A very important analysis on DNA chip data would be clustering genes to identify gene groups which have similar properties such as cancer. Clustering data for DNA chips usually deal with a large search space and has a very fuzzy characteristic. The Particle Swarm Optimization algorithm which was recently proposed is a very good candidate to solve such problems. In this paper, we propose a clustering mechanism that is based on the Particle Swarm Optimization algorithm. Our experiments show that the PSO-based clustering algorithm developed is efficient in terms of execution time for clustering DNA chip data, and thus be used to extract valuable information such as cancer related genes from DNA chip data with high cluster accuracy and in a timely manner.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.2
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• pp.36.1-36.1
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• 2018

Star formation activity of galaxies, along with color and morphology, show significant environmental dependence in local universe, where galaxies in dense environment tend to be more quiescent and redder. However, many studies show that such environmental dependence does not continue at higher redshifts beyond z~1. The question of how the environmental dependence of galactic properties have developed over time is crucial to understanding cosmic galactic evolution. By combining data from Canada-France-Hawaii Telescope Legacy Survey(CFHTLS), Infrared Medium-Deep Survey(IMS), and other surveys, the photometric redshifts of galaxies in CFHTLS W2 field were estimated by fitting spectral energy distribution. The distribution of galaxies was mapped in redshift bins of 0.05 interval from 0.6 to 1.4. For each redshift bin, the number density was mapped. The galaxies in high density regions were grouped into clusters using friend-of-friend method. The color of galaxies were analyzed to study the correlation with redshift as well as environmental difference between field galaxies and cluster member galaxies.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6D
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• pp.909-916
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• 2006

This study investigates tourists' sightseeing excursion behaviors and their information usage patterns at Fuji five lakes Area. This paper aims to empirically analyze the relationship between a sightseeing excursion behavior and use of tourist information applying a cluster analysis and a quantitative regression model. The main results are summarized as follows: (1) Tourists' information need is high about 90% of all tourists get information, 80% get the information before travel, 70% on the journey, 60% at the same time. (2) The patterns of information usage are categorized into 3 groups by the timing when tourists try to get the information.(3) There exists a difference among the time-spatial characteristics of excursion's behaviors such as the time after arriving time at sightseeing area, the time till go to home, duration time, and the total travel time between spots, the number of spots, and the size of excursion scale. (4) The quantitative regression model shows that information usage which constrained by time and space significantly determines both the number of the sightseeing spots and the duration time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3515-3538
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• 2015

Data accuracy can be increased by detecting and removing the incorrect data generated in wireless sensor networks. By increasing the data accuracy, network lifetime can be increased parallel. Network lifetime or operational time is the time during which WSN is able to fulfill its tasks by using microcontroller with on-chip memory radio transceivers, albeit distributed sensor nodes send summary of their data to their cluster heads, which reduce energy consumption gradually. In this paper a powerful algorithm using proactive fuzzy system is proposed and it is a mixture of fuzzy logic with comparative correlation techniques that ensure high data accuracy by detecting incorrect data in distributed wireless sensor networks. This proposed system is implemented in two phases there, the first phase creates input space partitioning by using robust fuzzy c means clustering and the second phase detects incorrect data and removes it completely. Experimental result makes transparent of combined correlated fuzzy system (CCFS) which detects faulty readings with greater accuracy (99.21%) than the existing one (98.33%) along with low false alarm rate.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.78.1-78.1
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• 2012

We have studied the physical properties of X-ray point sources in galaxy clusters using ~600 Chandra archival observations. The goal of this study is to investigate the density environmental effects on the physical properties of X-ray point sources by comparing the properties of X-ray point sources in galaxy clusters to those in typical blank fields. In this presentation, we show the nature of X-ray point sources which are expected to be related with galaxy clusters with different core properties. Using ~60 galaxy clusters observed with Chandra, we investigate the physical properties of X-ray point sources in cool-core and non-cool-core clusters. The cool-core clusters are known to have short central cooling time, and are characterized by low central entropy, systematic central temperature drops, and a brightest cluster galaxy at the X-ray peak. While the non-cool-core clusters have longer central cooling time, and are characterized by large central entropies and flat or centrally rising temperature profile. We show that how central core properties of galaxy clusters affect on the physical properties of X-ray point sources.