• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.1079-1094
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• 2014

In this paper, we study efficient gene selection methods by using conditional mutual information. We suggest gene selection methods using conditional mutual information based on semiparametric methods utilizing multivariate normal distribution and Edgeworth approximation. We compare our suggested methods with other methods such as mutual information filter, SVM-RFE, Cai et al. (2009)'s gene selection (MIGS-original) in SVM classification. By these experiments, we show that gene selection methods using conditional mutual information based on semiparametric methods have better performance than mutual information filter. Furthermore, we show that they take far less computing time than Cai et al. (2009)'s gene selection but have similar performance.

• Journal of Intelligence and Information Systems
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• v.15 no.2
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• pp.1-13
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• 2009

Scene classification and concept-based procedures have been the great interest for image categorization applications for large database. Knowing the category to which scene belongs, we can filter out uninterested images when we try to search a specific scene category such as beach, mountain, forest and field from database. In this paper, we propose an adaptive segmentation method for real-world natural scene classification based on a semantic modeling. Semantic modeling stands for the classification of sub-regions into semantic concepts such as grass, water and sky. Our adaptive segmentation method utilizes the edge detection to split an image into sub-regions. Frequency of occurrences of these semantic concepts represents the information of the image and classifies it to the scene categories. K-Nearest Neighbor (k-NN) algorithm is also applied as a classifier. The empirical results demonstrate that the proposed adaptive segmentation method outperforms the Vogel and Schiele's method in terms of accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.7
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• pp.956-962
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• 2018

As the study of the object feature detection from image, we explain methods to identify the species of the tree in forest using the picture taken from dron. Generally there are three kinds of methods, which are GLCM (Gray Level Co-occurrence Matrix) and Gabor filters, in order to extract the object features. We proposed the object extraction method using the statistical properties of trees in this research because of the similarity of the leaves. After we extract the sample images from the original images, we detect the objects using cross correlation techniques between the original image and sample images. Through this experiment, we realized the mean value and standard deviation of the sample images is very important factor to identify the object. The analysis of the color component of the RGB model and HSV model is also used to identify the object.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.5
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• pp.359-368
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• 2013

Mashup is a web application that combines several different sources to create new services using Open APIs(Application Program Interfaces). Although the mashup has become very popular over the last few years, there are several challenging issues when combining a large number of APIs into the mashup, especially when composite APIs are manually integrated by mashup developers. This paper proposes a novel algorithm for automatic Open API composition. The proposed algorithm consists of constructing an operation connecting graph and searching composition candidates. We construct an operation connecting graph which is based on the semantic similarity between the inputs and the outputs of Open APIs. We generate directed acyclic graphs (DAGs) that can produce the output satisfying the desired goal. In order to produce the DAGs efficiently, we rapidly filter out APIs that are not useful for the composition. The algorithm is evaluated using a collection of REST and SOAP APIs extracted from ProgrammableWeb.com.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.8
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• pp.18-24
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• 2017

The process of transmitting messages through a medium with a limited bandwidth or channel dispersion inevitably involves signal distortion and noise influxes, resulting in the degradation of transmission quality due to the inter-symbol interference and additional noise, which increases the error rate of the received symbols. The main role of the equalizer is to remove the channel distortion and noise from the received signal to recover the transmitted messages. A number of studies on the equalizer composed of a combination of linear filter and error control coding have shown that they played a key role in enhancing the transmission efficiency, which is essential for digital communication. This paper proposes a new algorithm to correct the residual symbol errors in the message signal. In general, equalizer performance improvement algorithms were developed to improve the initial convergence speed or steady-state error. In this paper, however, the equalizer input signal was reconstructed using the equalizer decision symbols and the channel estimates to directly correct the decision errors by analyzing the statistical characteristics of the difference signal between the actual received signal and the reconstructed signal.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.313-315
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• 2010

In this paper, we describe research results of developing hardware rasterizer that is applicable to mobile 3D graphics system, designed in SIMD architecture and verified in FPGA. Tile-based scan conversion unit is designed like SIMD architecture running four tiles simultaneously and each tile traverses pixels hierarchical in 3-level so that visiting counts is minimized. As experimental results, $8{\times}8$ is the most efficient size of tile and the last step of tile traversing is performed on $2{\times}2$ sized subtile. The rasterizer supports flat shading and gouraud shading and texture mapper supports affine mapping and perspective corrected mapping. Also, texture mapper supports point sampling mode and bilinear interpolating sampling mode and two types of wrapping modes and various blending modes. The rasterzer operates as 120Mhz on xilinx vertex4 $l{\times}100$ device. To easy verification, texture memory and frame buffer are generated as block rom and block ram.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.7
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• pp.1321-1327
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• 2009

In this paper, as the mobile communication service is widely used and the demand for wireless repeaters is rapidly increasing because of the easiness of extending service areas. But a wireless repeater has a problem the oscillation due to feedback signal. We proposed a new hybrid interference canceller using the adaptive filter with CMA(Constant Modulus Algorithm)-Grouped LMS(Least Mean Square) algorithm in the adaptive interference canceller. The proposed interference canceller has better channel adaptive performance and a lower MSE(Mean Square Error) than conventional structure because it uses the cancellation method of Grouped LMS algorithm. The proposed detector uses the LMS algorithms with two different step size to reduce mean square error and to obtain fast convergence. This structure reduces the number of iterations for the same MSE performance and hardware complexity compared to conventional nonlinear interference canceller.

• The KIPS Transactions:PartC
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• v.8C no.6
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• pp.855-864
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• 2001

With the increasing importance and complexity of EC (Electronic Commerce) across the Internet, the need and expectation for intelligent software agents to support both consumers and suppliers through the whole process of EC are growing rapidly. To realize the intelligent EC. a multiagent based EC system. which includes foundational technologies such as the establishment of standard product ontology the definition of message and negotiation protocol and brockering, is required. In this paper we propose an intelligent EC System named ICOMA(Intelligent electronic CO mmerce system based on Multi-Agent) as an open infrastructure of multiagent-based EC. Concretely we have proposed. designed and implemented an architecture of multiagent-based EC system including 6-types of agents message protocol for inter-agent negotiation, personalized produst retrieval and filtering., We have confirmed the effectiveness of the system through experiments.

• Journal of Advanced Navigation Technology
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• v.17 no.6
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• pp.726-735
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• 2013

This paper proposed face recognition methods about performance improvement of the face recognition using the properties of wavelet transform. Using discrete wavelet transform is Daubechies D4 filter that is similar to mother wavelet transform. For discrete wavelet transform method, In this case, by using LL subband only we can reduce processing time and amount of memory in recognition processing. To improve recognition ratio without further loss of 2 dimensional data changing, We applies 2D LDA. We perform SVM training algorithm to the feature vector obtained by 2D LDA. Experiment is performed using ORL database set and Yale database set by Matlab program. Test result shows that proposed method is superior to existence methods in recognition rate and performance time.

• The KIPS Transactions:PartB
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• v.17B no.3
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• pp.227-232
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• 2010

This paper proposes the real time lip reading method in the embedded environment. The embedded environment has the limited sources to use compared to existing PC environment, so it is hard to drive the lip reading system with existing PC environment in the embedded environment in real time. To solve the problem, this paper suggests detection methods of lip region, feature extraction of lips, and awareness methods of phonetic words suitable to the embedded environment. First, it detects the face region by using face color information to find out the accurate lip region and then detects the exact lip region by finding the position of both eyes from the detected face region and using the geometric relations. To detect strong features of lighting variables by the changing surroundings, histogram matching, lip folding, and RASTA filter were applied, and the properties extracted by using the principal component analysis(PCA) were used for recognition. The result of the test has shown the processing speed between 1.15 and 2.35 sec. according to vocalizations in the embedded environment of CPU 806Mhz, RAM 128MB specifications and obtained 77% of recognition as 139 among 180 words were recognized.