• Journal of the Korea Society of Computer and Information
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• v.16 no.8
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• pp.137-146
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• 2011

In order to support increased consumer awareness regarding energy consumption, we present new ways of monitoring and predicting with energy in electric appliances. The proposed system is a design of a common electrical power outlet called smart plug that measures the amount of current passing through current sensor at 0.5 second. To acquire data for training and testing the proposed neural network, weather parameters used include average temperature of day, min and max temperature, humidity, and sunshine hour as input data, and power consumption as target data from smart plug. Using the experimental data for training, the neural network model based on Back-Propagation algorithm was developed. Multi layer perception network was used for nonlinear mapping between the input and the output data. It was observed that the proposed neural network model can predict the power consumption quite well with correlation coefficient was 0.9965, and prediction mean square error was 0.02033.

• The Journal of Society for e-Business Studies
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• v.15 no.4
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• pp.101-121
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• 2010

This paper presents an intelligent prefetching technique that significantly improves performance of hybrid fash-disk storage, a combination of flash memory and hard disk. Since flash memory embedded in a hybrid device is much faster than hard disk in terms of I/O operations, it can be utilized as a 'cache' space to improve system performance. The basic strategy for prefetching is to utilize sequential pattern mining, with which we can extract the access patterns of objects from historical access sequences. We use two techniques for enhancing the performance of hybrid storage with prefetching. One of them is to modify a FAST algorithm for mapping the flash memory. The other is to extend the unit of prefetching to a block level as well as a file level for effectively utilizing flash memory space. For evaluating the proposed technique, we perform the experiments using the synthetic data and real UCC data, and prove the usability of our technique.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.646-650
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• 2014

In this paper, in order to avoid the deterioration of the pattern classification performance which results from the curse of dimensionality, we propose a new feature selection method. The newly proposed feature selection method is based on Fuzzy C-Means clustering algorithm which analyzes the data points to divide them into several clusters and the concept of a function with fuzzy numbers. When it comes to the concept of a function where independent variables are fuzzy numbers and a dependent variable is a label of class, a fuzzy number should be related to the only one class label. Therefore, a good feature is a independent variable of a function with fuzzy numbers. Under this assumption, we calculate the goodness of each feature to pattern classification problem. Finally, in order to evaluate the classification ability of the proposed pattern classifier, the machine learning data sets are used.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.6
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• pp.1441-1446
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• 2014

For the escape from a maze, the cooperative method by robot swarm was proposed in this paper. The robots can freely move by collecting essential data and making a decision in the use of sensors; however, a central control system is required to organize all robots for the escape from the maze. The robots explore new mazes and then send the information to the system for analyzing and mapping the escaping route. Three issues were considered as follows for the effective escape by multiple robots from the mazes in this paper. In the first, the mazes began to divide and secondly, dead-ends should be blocked. Finally, after the first arrivals at the destination, a shortcut should be provided for rapid escaping from the maze. The parallel-escape algorithms were applied to the different size of mazes, so that robot swarm can effectively get away the mazes.

• The Journal of the Acoustical Society of Korea
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• v.36 no.1
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• pp.70-77
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• 2017

Bandwidth extension is a technique to improve speech quality, intelligibility and naturalness, extending from the 300 ~ 3,400 Hz narrowband speech to the 50 ~ 7,000 Hz wideband speech. In this paper, an Artificial Bandwidth Extension (ABE) module embedded in the Opus audio decoder is designed using the information of narrowband speech to reduce the computational complexity of LPC (Linear Prediction Coding) and LSF (Line Spectral Frequencies) analysis and the algorithm delay of the ABE module. We proposed a spectral envelope extension method using DBN (Deep Belief Network), one of deep learning techniques, and the proposed scheme produces better extended spectrum than the traditional codebook mapping method.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.11
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• pp.155-164
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• 2014

Local histogram equalization is one of the most popular ways of enhancing the local brightness features of an input image. However, local histogram equalization reveals some problems. First, undesired artifacts are produced by over-enhancing the local features. Second, the enhancement of local features does not always result in global contrast enhancement. To cope with these problems, we propose an illumination driven local histogram equalization method. First, to estimate the illumination information, the proposed method combines the input image and the blurred image produced through the process of the down-sampling and the up-sampling. Next, the proposed method adaptively adjusts the mapping function estimated by the local histogram equalization using the information of the illumination. As a result, the proposed illumination information driven local histogram equalization method simultaneously enhances the global and the local contrast levels while preventing any local artifacts. Experimental results show that the proposed algorithm outperforms the conventional methods on objective and subjective criteria.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.5
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• pp.1-10
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• 2000

In this paper, we propose a Fuzzy Classifier System(FCS) makes the classifier system be able to carry out the mapping from continuous inputs to outputs. The FCS is based on the fuzzy controller system combined with machine learning. Therefore the antecedent and consequent of a classifier in FCS are the same as those of a fuzzy rule. In this paper, the FCS modifies input message to fuzzified message and stores those in the message list. The FCS constructs rule-base through matching between messages of message list and classifiers of fuzzy classifier list. The FCS verifies the effectiveness of classifiers using Bucket Brigade algorithm. Also the FCS employs the Genetic Algorithms to generate new rules and modify rules when performance of the system needs to be improved. Then the FCS finds the set of the effective rules. We will verify the effectiveness of the poposed FCS by applying it to Autonomous Mobile Robot avoiding the obstacle and reaching the goal.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.1
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• pp.112-121
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• 2016

AFLS (Adaptive front lighting system) is being applied to improve safety in driving automotive at night. Safe embedded system design for controlling head-lamps is required to improve noise robust ECU hardware and software simultaneously by considering safety requirement of hardware-dependent software under severe environmental noise. In this paper, we propose an adaptive headlight controller with a newly-designed symmetric angle sensor compensator, especially based on the proposed steering-swivel angle lookup table to determine whether the current controlling target is safe. The proposed system includes an additional backup hardware to compare the system status and provides safe swivel-angle management using a controlling algorithm based on the pre-defined lookup table (LUT), which is a symmetric mapping relationship between the requested steering angle and expected swivel angle target. The implemented system model shows that the proposed architecture effectively detects abnormal situations and restores safe status of controlling the light-angle in AFLS operations under severe noisy environment.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.1
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• pp.15-22
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• 2005

In this paper, we propose a face recognition system by using the CCD color image. We first get the face candidate image by using YCbCr color model and adaptive skin color information. And we use it initial curve of active contour model to extract face region. We use the Eye map and mouth map using color information for extracting facial feature from the face image. To obtain center point of Log-polar image, we use extracted facial feature from the face image. In order to obtain feature vectors, we use extracted coefficients from DCT and wavelet transform. To show the validity of the proposed method, we performed a face recognition using neural network with BP learning algorithm. Experimental results show that the proposed method is robuster with higher recogntion rate than the conventional method for the rotation and scale variant.

• Journal of KIISE:Databases
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• v.31 no.3
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• pp.307-319
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• 2004

Recently, ebXML and Web Services are emerging as the XML-based electronic business frameworks. To provide a set of registry services which users or applications can store and search the business information, ebXML and Web Services use ebXML registry and UDDI registry, respectively. They use the different registries each other, but there are something that similiar to the structure and functions of both of registries. In this paper, we analyze the similarity of ebXML Registry Information Model(RIM) and UDDI data structure, and construct the mapping information. So, we design and implement the UDDI Service Middleware which translates the request of UDDI registry service into the request of ebXML registry service using the algorithm. Consequently, we could use the ebXML registry like ebXML registry as well as UDDI registry without any changes in the ebXML registry itself so that we can not need to have both of registries for e-business.