• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.373-384
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• 2014

Data mining is to clarify pattern or correlation of mass data of complicated structure and to predict the diverse outcomes. This technique is used in the fields of finance, telecommunication, circulation, medicine and so on. In this paper, we selected risk factors of respiratory diseases in the field of medicine. The data we used was divided into respiratory diseases group and health group from the Gyeongsangbuk-do database of Community Health Survey conducted in 2012. In order to select major risk factors, we applied data mining techniques such as neural network, logistic regression, Bayesian network, C5.0 and CART. We divided total data into training and testing data, and applied model which was designed by training data to testing data. By the comparison of prediction accuracy, CART was identified as best model. Depression, smoking and stress were proved as the major risk factors of respiratory disease.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.97-105
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• 2015

Content-adaptive steganography methods embed secret messages in hard-to-model regions of covers such as complicated texture or noisy area. Content-adaptive steganalysis methods often need high dimensional features to capture more subtle relationships of local dependencies among adjacent pixels. However, these methods require many computational complexity and depend on the location of hidden message and the exploited distortion metrics. In this paper, we propose an improved steganalysis method for content-adaptive steganography to enhance detection rate with small number features. We first show that the features form the difference between DCT coefficients are useful for analyzing the content-adaptive steganography methods, and present feature extraction mehtod using first-order Markov probability for the the difference between DCT coefficients. The extracted features are used as input of ensemble classifier. Experimental results show that the proposed method outperforms previous schemes in terms of detection rates and accuracy in spite of a small number features in various content-adaptive stego images.

• Korean Journal of Construction Engineering and Management
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• v.6 no.6 s.28
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• pp.171-180
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• 2005

Public rental housing is constructed, owned, and managed by the public sector. The public institution for the public rental housing controls the whole building life cycle from the construction to the demolition. The construction company for the house built for sale is strongly interested in the cost for the initial investment, while the public institution is more focused on the maintenance cost for the preservation of the buildings Nevertheless, the maintenance cost of the public rental housing has been only managed as the accounting factor without the systemic research and analysis on the actual condition. This paper shows how expenses are related to the degree of obsolescence and presents the differences of the maintenance costs by the housing area and expenditure trends (vs time) of the maintenance costs, through analyzing time series data of public rental housing maintenance cost. Further, this paper helps understanding the causes of the differences of the maintenance costs by housing areas and characteristics of the expenditure trends. After all, this paper contributes to the improvement of the reliability and the practicality for the Life Cycle Cost modeling and the maintenance cost estimating.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.4
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• pp.401-411
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• 2008

Folksonomy, which is created through the collaborative tagging from many users, is one of the driving factors of Web 2.0. Tags are said to be the web metadata describing a web document. If we are able to find the semantic subsumption relationships between tags created through the collaborative tagging, it can help users understand the metadata more intuitively. In this paper, targeting del.icio.us tag data, we propose a method named FolksoViz for deriving subsumption relationships between tags by using Wikipedia texts. For this purpose, we propose a statistical model for deriving subsumption relationships based on the frequency of each tag on the Wikipedia texts, and TSD(Tag Sense Disambiguation) method for mapping each tag to a corresponding Wikipedia text. The derived subsumption pairs are visualized effectively on the screen. The experiment shows that our proposed algorithm managed to find the correct subsumption pairs with high accuracy.

• Smart Media Journal
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• v.1 no.2
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• pp.12-22
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• 2012

Today we are witnessing an increasingly widespread use of cameras in our lives for video surveillance, robot vision, and mobile phones. This has led to a renewed interest in computer vision in general and an on-going boom in human activity recognition in particular. Although not particularly fancy per se, human gait is inarguably the most common and frequent action. Early on this decade there has been a passing interest in human gait recognition, but it soon declined before we came up with a systematic analysis and understanding of walking motion. This paper presents a set of DBN-based models for the analysis of human gait in sequence of increasing complexity and modeling power. The discussion centers around HMM-based statistical methods capable of modeling the variability and incompleteness of input video signals. Finally a novel idea of extending the discrete state Markov chain with a continuous density function is proposed in order to better characterize the gait direction. The proposed modeling framework allows us to recognize pedestrian up to 91.67% and to elegantly decode out two independent gait components of direction and posture through a sequence of experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.7
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• pp.1457-1467
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• 2015

Depending on the type of Tx-Rx pairs, VHF Data Exchange System (VDES) for maritime communication is expected to employ the different frequency channels. Load imbalance between the different channels turns out to be a critical problem for the multi-hop communication using Ad-hoc Self-Organizing TDMA (ASO-TDMA) MAC protocol, which has been proposed to provide the connectivity between land station and remote ship stations. In order to handle the inter-channel load imbalance problem, we consider a model of the stochastic geomety in this paper. After analyzing the spatial reuse efficiency in each hop region by the given model, we show that the resource utility can be maximized by balancing the inter-channel traffic load with optimal resource allocation in each hop region.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.2C
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• pp.181-187
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• 2012

Millimeter wave (MMW) readily penetrates fabrics, thus it can be used to detect objects concealed under clothing. A passive MMW imaging system can operate as a stand-off type sensor that scans people in both indoors and outdoors. However, because of the diffraction limit and low signal level, the imaging system often suffers from low image quality. Therefore, suitable statistical analysis and computational processing would be required for automatic analysis of the images. In this paper, a real-time concealed object detection is addressed by means of the multi-level segmentation. The histogram of the image is modeled with a Gaussian mixture distribution, and hidden object areas are segmented by a multi-level scheme involving $k$-means, the expectation-maximization algorithm, and a decision rule. The complete algorithm has been implemented in C++ environments on a standard computer for a real-time process. Experimental and simulation results confirm that the implemented system can achieve the real-time detection of concealed objects.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.8 no.4
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• pp.390-402
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• 1997

The ignition noises from the vehicle are measured and the measurement data are statistically treated for modeling. The low-noise amplifier and band-pass filter are added between the receiver and the three axes antenna for low noise level measurement and the APD and PSD are measured in 800 MHz frequency range. The measured APD curves can be expressed in terms of sensitivity study of each model through 3(class A) or 6(Class B) parameters variation, and these optimal parameter can easily be calculated by using the Composite Approximation Algorithm. The selected APD parameter can be used for making the Data Base EM-environments and also applied to determine the output and sensitivity margin for the transmitter and receiver. 'Digital microwave transmission systems are equipped with equalizer against fading during multipath fading. In this paper, we proposed variable reference tap position equalizer that varies the reference tap according to fading type to archive better performance. We got the perf？mance improvement about 4~5 dB in MP condition and 2~3 dB in NMP condition from simulation results.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.153-162
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• 2009

This paper suggests the novel light-weight signal processing algorithm for wireless sensor network applications which needs low computing complexity and power consumption. Exponential average method (EA) is utilized by real time, to process the magnetometer signal which is analyzed to understand the own physical characteristic in time domain. EA provides the robustness about noise, magnetic drift by temperature and interference, furthermore, causes low memory consumption and computing complexity for embedded processor. Hence, optimal parameter of proposal algorithm is extracted by statistical analysis. Using general and precision magnetometer, detection probability over 90% is obtained which restricted by 5% false alarm rate in simulation and using own developed magnetometer H/W, detection probability over 60~70% is obtained under 1~5% false alarm rate in simulation and experiment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.8B
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• pp.1424-1435
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• 2000

A bit-rate controller that can achieve a constant bit rate when coding object-based video sequences is an important part to achieve an adaptation to bit-rate constraints, desired video quality, distribution of bits among objects, relationship between texture and shape coding, and determination of frame skip or not. Therefore we design content-based bit rate controller which will be used for relevant bit-rate control. The implementation is an extension of MPEG-4 rate control algorithm which employs a quadratic rate-quantizer model. The importance of different objects in a video is analyzed and segmented into a number of VOPs which are adaptively bit-allocated using the object-based modelling. Some test sequences are observed by a number of non-experts and interests in each object are analysed. The initial total target bit-rate for all objects is obtained by using the proposed technique. Then the total target bits are jointly analyzed for preventing from overflow or underflow of the buffer fullness. The target bits are distributed to each object in view of its importance, not only of statistical analysis such as motion vector magnitude, size of object shape, and coding distortion of previous frame. The scheme is compared with the rate controller adopted by the MPEG-4 VM8 video coder by representing their statistics and performance.