• Journal of the military operations research society of Korea
• /
• v.13 no.1
• /
• pp.1-18
• /
• 1987

This paper presents several adaptive linear predictive coding techniques based upon extension of recursive ladder filters. A 2-D recursive ladder filter is extended to a 3-D case which can adaptively track the variation of both spatial and temporal changes of moving images. Using the 2-D/3-D ladder filter and a previous farme predictor, two types of adaptive predictor-control schemes are proposed in which the prediction error at each pel can be obtained at or close to a minimum level. We also investigate several modifications of the basic encoding methods. Performance of the 2-D/3-D ladder filters, their adaptive control schemes, and variations in coding methods are evaluated by computer simulations on a real sequence and compared to the results of motion compensation and frame differential coders. As a validity test of the ladder filters developed, the error signals for the different predictors are compared and evaluated.

• Journal of Korean Society of Transportation
• /
• v.19 no.6
• /
• pp.143-160
• /
• 2001

Micro-simulation models have been recognized as an efficient assessment tool in developing traffic signal control technologies. In this paper a prototype of a microscopic simulation model which can be applied to evaluate the performance of traffic-adaptive signal control strategies was developed. In the simulation process, space-based arrays were appled to estimate parameters of car following and lane changing models. Two levels of link types, a micro-type and macro-type links, were also embodied in the simulation process. The proposed model was tested on a test network consists of 9 intersections. The performance of the proposed model was evaluated in link by link comparisons with the results of NETSIM. The results show that the proposed model could appropriately simulate traffic flows of the test network. The model also produces traffic adaptive signal timings, cycle lengths and green times for turning movements, based on the detector data. It implies that the optimization process of the model produces reasonable signal timings for the test network on the cycle basis.

• Asia-Pacific Journal of Business
• /
• v.14 no.3
• /
• pp.67-88
• /
• 2023

Purpose - This study examined the effect of empowering leadership on adaptive performance and verified the mediating effect of job challenge in the relationship between empowering leadership and adaptive performance. Additionally, this study investigated the moderating effect of agentic and communal traits in the relationship between supervisor's empowering leadership and adaptive performance of subordinates. Design/methodology/approach - This study used data collected from 279 participants via an online platform. Multiple regression analysis, bootstrapping, hierarchical regression analysis, and simple slope test were used to analyze the data. Findings - First, supervisor's empowering leadership had a positive effect on adaptive performance. Second, job challenge was found to mediate the relationship between supervisor's empowering leadership and adaptive performance. Third, the agentic trait showed a moderating effect on strengthening the relationship between supervisor's empowering leadership and adaptive performance. However, communal trait did not show a moderating effect. Research implications or Originality - This study examined the moderating effect of agentic traits in the relationship between empowering leadership and adaptive performance, which has not been investigated before.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2004.10a
• /
• pp.542-549
• /
• 2004

The compressive strength of concrete is commonly used criterion in producing concrete. However, the tests on the compressive strength are complicated and time-consuming. More importantly, it is too late to make improvement even if the test result does not satisfy the required strength, since the test is usually performed at the 28th day after the placement of concrete at the construction site. Therefore, accurate and realistic strength estimation before the placement of concrete is being highly required. In this study, the estimation of the compressive strength of concrete was performed by probabilistic neural network (PNN) on the basis of concrete mix proportions. The estimation performance of PNN was improved by considering the correlation between input data and targeted output value. Adaptive probabilistic neural network (APNN) was proposed to automatically calculate the smoothing parameter in the conventional PNN by using the scheme of dynamic decay adjustment algorithm. The conventional PNN and APNN were applied to predict the compressive strength of concrete using actual test data of a concrete company. APNN showed better results than the conventional PNN in predicting the compressive strength of concrete.

• Journal of the Korea Society for Simulation
• /
• v.20 no.3
• /
• pp.19-28
• /
• 2011

Adaptive Random Testing (ART) aims to enhance the performance of pure random testing by detecting failure region in a software. The ART algorithm generates effective test cases which requires less number of test cases than that of pure random testing. However, all ART algorithms currently proposed are designed for the tests of monolithic system or unit level. In case of integrated system tests, ART approaches do not achieve same performances as those of ARTs applied to the unit or monolithic system. In this paper, we propose an extended ART algorithm which can be applied to the integrated system testing environment without degradation of performance. The proposed approach investigates an input distribution of the unit under a test with limited number of seed input data and generates information to be used to resizing input domain partitions. The simulation results show that our approach in an integration environment could achieve similar level of performance as an ART is applied to a unit testing. Results also show resilient effectiveness for various failure rates.

• Journal of Digital Convergence
• /
• v.15 no.12
• /
• pp.661-667
• /
• 2017

The purpose of this study is to examine the effects of therapeutic horse riding on adult with intellectual disability in terms of adaptive behavior. The subjects were 16 adults with intellectual disability. They participated in a therapeutic horse riding program of 60 minutes long, Twice a week for 12 weeks. The participants' adaptive behavior level were measured before and after 12 weeks of program with Social Maturity Scale. The data was analyzed by paired t-test using the SPSS. After 12 weeks of therapeutic horse riding program, there was a significant improvements on self-help, task, self-regulation & socialization. However, locomotion, communication changes did not reach statistical significance. The result indicates that therapeutic horse riding has a positive effect on adults with intellectual disability in self-help, task, self-regulation & socialization. This study suggests that therapeutic horse riding could be considered an effective method on adults with intellectual disability to improve adaptive behavior.

• Proceedings of the Korean Society of Computational and Applied Mathematics Conference
• /
• 2002.09a
• /
• pp.12-12
• /
• 2002

• Journal of the Korea Society of Computer and Information
• /
• v.9 no.1
• /
• pp.63-70
• /
• 2004

This paper describes modeling, design and performance test results of infrared thermal image target system which can generate infrared thermal image on aircraft. The system is designed to control image shape and intensity so that the infrared image shape and its emitting intensity are so similar to that of real aircraft. When applying the technique suggested in this paper, the system consumes only small electric power energy about 30(㎾) to generate infrared thermal image which is equivalent to that of real aircraft under full power operation. After verifying performance test, the system developed here has been used as a target for korean potable surface to air missile(KPSAM) at the stage of evaluation test such as target adaptive guidance test and auto-pilot logic test.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.2065-2069
• /
• 2004

This paper presents an adaptive equalizer using finite impulse response (FIR) filter and least-mean square (LMS) algorithm. Herein, the variable step-size technique (VSLMS) for compensating the amplitude of chrominance signal is utilized. The proposed equalizer can be enhanced and compressed the chrominance signal at color subcarrier. The LMS algorithm employed in simplicity structure but gives slow convergence speed. Thus, the variable step-size is very attractive algorithm due to its computational efficiencies and the speed of convergence is improved. In addition, experimental results are carried out by using the modulated 20T sine squared test signal. It is shown here that the adaptive equalizer can be equalized the amplitude chrominance distortion in color television transmission without relative delay distortion.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.7
• /
• pp.3095-3111
• /
• 2018

Spectrum sensing (SS) is one of the fundamental tasks for cognitive radio. In SS, decisions can be made via comparing the test statistics with a threshold. Conventional adaptive algorithms for SS usually adjust their thresholds according to the radio environment. This paper concentrates on the issue of adaptive SS whose threshold is adjusted based on the Markovian behavior of primary user (PU). Moreover, Bayesian cost is adopted as the performance metric to achieve a trade-off between false alarm and missed detection probabilities. Two novel adaptive algorithms, including Markov Bayesian energy detection (MBED) algorithm and IMBED (improved MBED) algorithm, are proposed. Both algorithms model the behavior of PU as a two-state Markov process, with which their thresholds are adaptively adjusted according to the detection results at previous slots. Compared with the existing Bayesian energy detection (BED) algorithm, MBED algorithm can achieve lower Bayesian cost, especially in high signal-to-noise ratio (SNR) regime. Furthermore, it has the advantage of low computational complexity. IMBED algorithm is proposed to alleviate the side effects of detection errors at previous slots. It can reduce Bayesian cost more significantly and in a wider SNR region. Simulation results are provided to illustrate the effectiveness and efficiencies of both algorithms.