• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.1
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• pp.116-125
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• 2014

Road conditions can provide important information for driving safety in driving assistance systems. The input images usually include unnecessary information and they need to be analyzed only in a region of interest (ROI) to reduce the amount of computation. In this paper, a vision-based road ROI determination algorithm is proposed to detect the road region using the positional information of a vanishing point and line segments. The line segments are detected using Canny's edge detection and Hough transform. The vanishing point is traced by a Kalman filter to reduce the false detection due to noises. The road ROI can be determined automatically and adaptively in every frame after initialization. The proposed method is implemented using C++ and the OpenCV library, and the road ROIs are obtained from various video images of black boxes. The results show that the proposed algorithm is robust.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.41-46
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• 2011

The tire damage classification method is researched by periodicity detection of ultrasonic envelope signals to occur at the driving vehicle tire. Because periodic signals is generated by rotations of the damaged tire, it should convert to pulse for using the density function. After time intervals of pulses are represented by the density function, the dominant periodicity is detected. The threshold to make a pulse is calculated by moving average of envelope signals. The result of time density function in case of one damage material, the first peak's time is equals to tire's rotation period, 162ms and 102ms, about the speed of 50km/h and 80km/h. In case of more than one damage material, the sum of each peak's time is equals to tire's rotation period about the speed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.284-294
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• 2018

Statistical methods have been widely used to estimate the remaining battery runtime of mobile smart devices, such as smart phones, smart gears, tablets, and etc. However, existing work available in the literature only considers a particular statistical method. Thus, it is difficult to determine whether statistical methods are applicable to estimating thr remaining battery runtime of mobile devices or not. In this paper, we evaluated the performance of statistical methods applicable to estimating the remaining battery runtime of mobile smart devices. The statistical estimation methods evaluated in this paper are as follows: simple and moving average, linear regression, multivariate adaptive regression splines, auto regressive, polynomial curve fitting, and double and triple exponential smoothing methods. Research results presented in this paper give valuable data of insight to IT engineers who are willing to deploy statistical methods on estimating the remaining battery runtime of mobile smart devices.

• Journal of Korea Game Society
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• v.16 no.5
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• pp.99-110
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• 2016

This paper proposes the adaptive way that intended screen applies the same proportion of the game screen to mobile devices having various resolution. Generally speaking, clipping is the way to show only part of screen with designated proportion and is widely used in game industry. It costs additionally because developers make game screens fit various resolutions. However, the proposed method of this study saves developing time and cost if automatically calculated output is possible according to designated screen proportion and devices' aspect ratio. This suggested algorithm makes it possible to display game screen in same proportion automatically to various resolution and the mini-map is automatically fixed regardless of the mobile devices' resolution.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1311-1327
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• 2016

We propose a multi-state model for analyzing semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the 'illness-death model', which composes three states, such as 'healthy', 'diseased', and 'dead'. The state of 'diseased' can be considered as an intermediate event. Two more states are added into the illness-death model to describe missing events caused by a loss of follow-up before the end of the study. One of them is a state of 'LTF', representing a lost-to-follow-up, and the other is an unobservable state that represents the intermediate event experienced after LTF occurred. Given covariates, we employ the Cox proportional hazards model with a normal frailty and construct a full likelihood to estimate transition intensities between states in the multi-state model. Marginalization of the full likelihood is completed using the adaptive Gaussian quadrature, and the optimal solution of the regression parameters is achieved through the iterative Newton-Raphson algorithm. Simulation studies are carried out to investigate the finite-sample performance of the proposed estimation procedure in terms of the empirical coverage probability of the true regression parameter. Our proposed method is also illustrated with the dataset adapted from Helmer et al. (2001).

• Journal of Broadcast Engineering
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• v.20 no.1
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• pp.40-47
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• 2015

This paper discusses QoS enhancement in the Best-effort services of the service plan provided by MPEG Media Transport (MMT) systems for video streaming applications. Among MMT services, i.e. per-flow, per-class, and best-effort services, the server does not provide guaranteed bandwidth for the best-effort service only. Therefore, in the best-effort services, a bandwidth access priority is defined for various services, where the lowest priority is assigned to the low-level video services. To alleviate the issue of bandwidth limitation in the best-effort services, this paper investigates transmission of low-resolution video with low bitrate and up-sampling. Our experimental results prove the superiority of the proposed method in terms of delivered video quality.

• Journal of Broadcast Engineering
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• v.23 no.4
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• pp.495-502
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• 2018

JVET (Joint Video Exploration Team) which explored evolving technologies of video coding with capabilities beyond HEVC (High Efficiency Video Coding), released a references software codec named the Joint Exploration Model (JEM) for performance verification of coding technologies. JEM has 67 intra prediction modes that extend the 35 modes of HEVC for intra prediction. Therefore, the enhancement of the coding performance is limited due to the overhead of prediction mode coding. In this paper, we analyze the probabilities of prediction modes selections, and then we propose a more efficient intra prediction mode coding based on the results of analyzed mode occurrence. In addition, we propose a context modeling for CABAC (Context-Adaptive Binary Arithmetic Coding) of the proposed mode coding. Experimental results show that the BD-rate gain is 0.02% on the AI (All Intra) coding structure compared to JEM 7.0. We need to optimize context modeling for additional coding performance enhancement.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.12
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• pp.2530-2538
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• 2015

The pixel value of depth image is depth value so that different objects which are placed on nearby position have similar pixel value. Moreover, the pixels of depth image have distinct pixel values compared to adjacent pixels while those of color image has very similar values. Accordingly distorted depth image of multiview video plus depth (MVD) needs proper error concealment methods considering the characteristics of depth image when transmission errors are happened. In this paper, classifying regions of depth image to consider edge directions and then applying adaptive error concealment methods to each region are proposed. Recovered depth images utilize with multiview video data to synthesize intermediate-view point video. The synthesized view is evaluated by objective quality metrics to demonstrate proposed method performance.

• Journal of the korean Society of Automotive Engineers
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• v.14 no.6
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• pp.113-126
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• 1992

Recently the multi-kind, small-amount manufacturing system has been replacing the mass manufacturing system, and domestic machining inustry also is eager to absorb the new technology because of its high productivity and cost reduction. The optimization of the cutting condition has been a vital problem in the machining industry, which would help increase the productivity and raise the international competitiveness. It is intended in this study to investigate the machining costs per unit time which is essential to the analysis of the optimal cutting condition, to computer the cutting speed that lead to the minimum machining costs and the maximum production to suggest the cutting speed range that enables efficient speed cutting, and to review the machining economy in relation to cutting depth and feed. Also considered are the optimal cutting speed and prodution rated in rrelation with feed. It is found that the minimum-cost cutting speed increases and the efficient cutting speed range is reduced as machining cost per unit time increases since the cutting speed for maximum production remains almost constant. The machining cost is also lowered and the production rate increases as the feed increases, and the feed should be selected to satisfy the required surface roughness. The machining cost and production rate are hardly affected by the cutting depth if the cutting speed stays below 100m/min, however, they are subject to change at larger cutting depth and the high-efficient speed range also is restricted. It can be established an adaptive optimal cutting conditions can be established in workshop by the auto-selection progam for optimal operation. It is expected that this method for choosing the optimal cutting conditions might contribute to the improvement of the productivity and reduced the cost. It is highly recommended to prepare the optimal cutting conditionthus obtained for future use in the programing of G-function of CNC machines. If proper programs that automatically select the optimal cutting conditions should be developed, it would be helpful to the works being done in the machine shops and would result in noticeable production raise and cost reduction.

• The KIPS Transactions:PartB
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• v.16B no.4
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• pp.327-331
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• 2009

In fuzzy logic, aggregating uncertainties is generally achieved by means of operators such as t-norms and t-conorms. However, existing aggregation operators have some disadvantages as follows : First, they are situation-independent. Thus, they may not be properly applied to dynamic aggregation process. Second, they do not give an intuitional sense to decision making process. To solve these problems, we propose a new $\varepsilon$-AMDA (Aggregation based on the fuzzy Multidimensional Decision Analysis) algorithm to reflect degrees of strength for option i (i = 1, 2, ..., n) in the decision making process. The $\varepsilon$-AMDA algorithm makes adaptive aggregation results between min (the most weakness for an option) and max (the most strength for an option) according to the values of the parameter representing degrees of strength for an option. In this respect, it may be applied to dynamic aggregation process. In addition, it provides a mechanism of the fuzzy multidimensional decision analysis for decision making, and gives an intuitional sense to decision making process. Thus, the proposed method aids the decision maker to get a suitable decision according to the degrees of strength for options (or alternatives).