• Journal of Broadcast Engineering
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• v.22 no.3
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• pp.282-294
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• 2017

In this paper, we propose a novel intelligent headlight control (IHC) system which is durable to various road lights and camera movement caused by vehicle driving. For detecting candidate light blobs, the region of interest (ROI) is decided as front ROI (FROI) and back ROI (BROI) by considering the camera geometry based on perspective range estimation model. Then, light blobs such as headlights, taillights of vehicles, reflection light as well as the surrounding road lighting are segmented using two different adaptive thresholding. From the number of segmented blobs, taillights are first detected using the redness checking and random forest classifier based on Haar-like feature. For the headlight and taillight classification, we use the random forest instead of popular support vector machine or convolutional neural networks for supporting fast learning and testing in real-life applications. Pairing is performed by using the predefined geometric rules, such as vertical coordinate similarity and association check between blobs. The proposed algorithm was successfully applied to various driving sequences in night-time, and the results show that the performance of the proposed algorithms is better than that of recent related works.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.786-792
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• 2010

This paper presents a real-time lane detection method which can accurately find the lane-mark boundaries in complex road environment. Unlike many existing methods that pay much attention on the post-processing stage to fit lane-mark position among a great deal of outliers, the proposed method aims at removing those outliers as much as possible at feature extraction stage, so that the searching space at post-processing stage can be greatly reduced. To achieve this goal, a grid-based morphology operation is firstly used to generate the regions of interest (ROI) dynamically, in which a directional edge-linking algorithm with directional edge-gap closing is proposed to link edge-pixels into edge-links which lie in the valid directions, these directional edge-links are then grouped into pairs by checking the valid lane-mark width at certain height of the image. Finally, lane-mark colors are checked inside edge-link pairs in the YUV color space, and lane-mark types are estimated employing a Bayesian probability model. Experimental results show that the proposed method is effective in identifying lane-mark edges among heavy clutter edges in complex road environment, and the whole algorithm can achieve an accuracy rate around 92% at an average speed of 10ms/frame at the image size of $320{\times}240$.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.126-134
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• 2015

A sleep disorder is being recognized as one of the major health issues related to high levels of stress. At the same time, interests about quality of sleep are rapidly increasing. However, diagnosing sleep disorder is not a simple task because patients should undergo polysomnography test, which requires a long time and high cost. To solve this problem, an accelerometer embedded wrist-worn device is being considered as a simple and low cost solution. However, conventional methods determine a state of user to "sleep" or "wake" according to whether values of individual section's accelerometer data exceed a certain threshold or not. As a result, a high miss-classification rate is observed due to user's intermittent movements while sleeping and tiny movements while awake. In this paper, we propose a novel method that resolves the above problems by employing a dynamic classifier which evaluates a similarity between the neighboring data scores obtained from SVM classifier. A performance of the proposed method is evaluated using 50 data sets and its superiority is verified by achieving 88.9% accuracy, 88.9% sensitivity, and 88.5% specificity.

• Journal of the Korean earth science society
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• v.26 no.8
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• pp.790-799
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• 2005

We investigate the optical properties of aerosols over Gongju by an indirect method using the pound measurement, Sky-radiometer. The analysis period is from January to December, 2004. Skyrad. pack.3 is used to estimate the optical properties, such as the aerosol optical thickness (AOT), single scattering albedo (SSA), ${\AA}ngstron$ exponent $({\alpha})$ and size distribution, of aerosols from the ground measured radiance data. And qualify control is applied to minimize the cloud-contaminated data and improve the quality of analysis results. The 12-month average of AOT, ${\alpha}$, and SSA are 0.46, 1.14, and 0.91, respectively. The average volume spectra of aerosols shows a bi-modal distribution, the first peak at fine mode and the second peak at coarse mode. AOT and coarse particles clearly increases while SSA decreases during the Asian dust events. The optical properties of aerosols at Gongju vary with?seasons, but those are not influenced by the wind direction.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.651-656
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• 2014

Corrosion has a significant influence upon the reliability assessment and the maintenance planning of gas pipeline. Corrosion defects occurred on the underground pipeline can be obtained by conducting periodic in-line inspection (ILI). However, little study has been done for practical use of ILI data. This paper deals with remaining lifetime prediction of the gas pipeline in the presence of corrosion defects. Because a pipeline parameter includes uncertainty in its operation, a probabilistic approach is adopted in this paper. A pipeline fails when its operating pressure is larger than the pipe failure pressure. In order to estimate the failure probability, this paper uses First Order Reliability Method (FORM) which is popular in the field of structural engineering. A well-known Battelle code is chosen as the computational model for the pipe failure pressure. This paper develops a Matlab GUI for illustrating failure probability predictions Our result indicates that clustering of corrosion defects is helpful for improving a prediction accuracy and preventing an unnecessary maintenance.

• Journal of IKEEE
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• v.24 no.1
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• pp.25-32
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• 2020

In this paper, we propose an image generator for OLED panel test that can compensate for color coordinates and luminance by using panel defect inspection and optical measurement while displaying images on OLED panel. The proposed image generator consists of two processes: the image generation process and the process of compensating color coordinates and luminance using optical measurement. In the image generating process, the panel is set to receive the panel information to drive the panel, and the image is output by adjusting the output setting of the image generator according to the panel information. The output form of the image is configured by digital RGB method. The pattern generation algorithm inside the image generator outputs color and gray image data by transmitting color data to a 24-bit data line based on a synchronization signal according to the resolution of the panel. The process of compensating color coordinates and luminance using optical measurement outputs an image to an OLED panel in an image generator, and compensates for a portion where color coordinates and luminance data measured by an optical module differ from reference data. To evaluate the accuracy of the image generator for the OLED panel test proposed in this paper, Xilinx's Spartan 6 series XC6SLX25-FG484 FPGA was used and the design tool was ISE 14.5. The output of the image generation process was confirmed that the target setting value and the simulation result value for the digital RGB output using the oscilloscope matched. Compensating the color coordinates and luminance using optical measurements showed accuracy within the error rate suggested by the panel manufacturer.

• Journal of Digital Convergence
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• v.11 no.9
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• pp.289-299
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• 2013

The aim of this study was to enhance the NHI claims data-based tuberculosis classification rule of KCDC(Korea centers for disease control & prevention) for an effective TB surveillance system. 8,118 cases, 10% samples of 81,199 TB cases from NHI claims data during 2009, were subject to the Medical Record Survey about whether they are real TB patients. The final study population was 7,132 cases whose medical records were surveyed. The decision tree model was evaluated as the most superior TB patients detection model. This model required the main independent variables of age, the number of anti-tuberculosis drugs, types of medical institution, tuberculosis tests, prescription days, types of TB. This model had sensitivity of 90.6%, PPV of 96.1%, and correct classification rate of 93.8%, which was better than KCDC's TB detection model with two or more NHI claims for TB and TB drugs(sensitivity of 82.6%, PPV of 95%, and correct classification rate of 80%).

• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.6
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• pp.1234-1240
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• 2009

This study was to compare the effectiveness and validity of various data-mining algorithm for Sasang type diagnostic test. We compared the sensitivity and specificity index of nine attribute selection and eleven class classification algorithms with 31 data-set characterizing Sasang typology and 10-fold validation methods installed in Waikato Environment Knowledge Analysis (WEKA). The highest classification validity score can be acquired as follows; 69.9 as Percentage Correctly Predicted index with Naive Bayes Classifier, 80 as sensitivity index with LWL/Tae-Eum type, 93.5 as specificity index with Naive Bayes Classifier/So-Eum type. The classification algorithm with highest PCP index of 69.62 after attribute selection was Naive Bayes Classifier. In this study we can find that the best-fit algorithm for traditional medicine is case sensitive and that characteristics of clinical circumstances, and data-mining algorithms and study purpose should be considered to get the highest validity even with the well defined data sets. It is also confirmed that we can't find one-fits-all algorithm and there should be many studies with trials and errors. This study will serve as a pivotal foundation for the development of medical instruments for Pattern Identification and Sasang type diagnosis on the basis of traditional Korean Medicine.

• KIISE Transactions on Computing Practices
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• v.21 no.10
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• pp.658-669
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• 2015

The paradigm of game development changes with technological trends. If the system can analyze and determine undefined inputs, users' input choices are not restricted. Therefore, game scenarios can have multifarious flows depending upon the user's input data. In this paper, we propose a method of including an output plan in the game system that is based on the user's input but is not restricted to predefined choices. We have implemented an experimental game on the Android platform by combining network communication and APIs. The game interface works as follows: first, the user's input data is transmitted to the server using HTTP protocol; then, the server carries out an analysis on the input data; and finally, the server returns the decision result to the game device. The game can provide users a scenario that corresponds to the decision results. In this paper, we used an image file for the user's input data format. The server calculates similarities between the user's image file and reference images obtained from the Naver Image Search API and then returns determination results. We have confirmed the value of integrating the game development framework with other computing technologies demonstrating the potential of the proposed methods for application to various future game interfaces.

• Journal of Convergence for Information Technology
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• v.9 no.12
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• pp.141-146
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• 2019

Economic analysis predicts that the drone market will grow, and the growth of the toy and hobby drone market is expected to gradually expand. Drone expectations are rising due to the net economic function of drone market growth, but accidents due to improper management and operations are also increasing. The difference in toy drone performance is incomparably small compared to industrial drone performance, but the ordinary buyer can not know whether the difference can cause an accident during use. The toy drones used in this study were obtained from KC and CE certification, and 20 kinds of drones were used. The flight time ranged from a minimum of 3 minutes to a maximum of 12 minutes, and the control distance ranged from a minimum of 20m to a maximum of 380m. Therefore, it is necessary to secure product safety through sampling inspection of the radio wave output of toy drones, and it is also necessary to mount an algorithm that automatically lowers the altitude or hover when exceeding the limit flight distance. For future research, we will build data to establish toy drone safety standards through a altitude testing and impact testing of toy drone.