• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.4
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• pp.61-67
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• 2017

Low-dose X-ray fluoroscopic image sequences to avoid radiation exposure risk are contaminated by quantum noise. To restore these noisy sequences, we propose a 3D nonlocal means (NLM) filter based on stochastic distancesed can be applied to the denoising of X-ray fluoroscopic image sequences. The stochastic distance is obtained within motion-compensated noise filtering support to remove the Poisson noise. In this paper, motion-adaptive weight which reflected the frame similarity is proposed to restore the noisy sequences without motion artifact. Experimental results including comparisons with conventional algorithms for real X-ray fluoroscopic image sequences show the proposed algorithm has a good performance in both visual and quantitative criteria.

• Asian-Australasian Journal of Animal Sciences
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• v.23 no.4
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• pp.437-443
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• 2010

To be economically profitable, the poultry industry demands an increase in stocking density, which could adversely affect chicken welfare. The current study was performed to investigate the effect of stocking density on stress-related, heat shock protein genes (HSP70 and HSP90), 3-hydroxyl-3-methyl-glutaryl coenzyme A reductase (HMGCR) gene and telomere length in broiler chickens. Seven-day-old broiler chickens were housed at High (0.0578 $m^2$/bird), Standard (0.077 $m^2$/bird) and Low (0.116 $m^2$/bird) stocking densities with 8 replicates each until 35 d of age. The growth performance, such as body weight gain and average daily feed intake, was found to be significantly (p<0.05) higher in the Low density group, but these parameters did not show any difference between the High and Standard groups. Other growth performance, such as feed conversion ratio and final feed intake, showed no difference among the treated groups. The expression levels of HSP70 and HMGCR were found to be elevated with the increase of stocking density. The expression level of these genes was significantly (p<0.05) higher in the High density stocked group compared with the other groups, whereas the expression levels were not significantly different between the Low and Standard groups. The expression levels of HSP90 did not show any significant changes among the treated groups. The telomeric length of the birds housed in High density was reduced significantly (p<0.05) when compared to that of the birds in Low density. These results clearly indicate that birds stocked at high density show physiological adaptive changes indicative of stress at gene transcriptional and telomere levels.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4549-4567
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• 2016

To cope with the complex electromagnetic environment of wireless communication systems, anti-jamming decision methods are necessary to keep the reliability of communication. Basing on the rule-reduced genetic algorithm (RRGA), an anti-jamming decision method is proposed in this paper to adapt to the fast channel variations. Firstly, the reduced decision rules are obtained according to the rough set (RS) theory. Secondly, the randomly generated initial population of the genetic algorithm (GA) is screened and the individuals are preserved in accordance with the reduced decision rules. Finally, the initial population after screening is utilized in the genetic algorithm to optimize the communication parameters. In order to remove the dependency on the weights, this paper deploys an anti-jamming decision objective function, which aims at maximizing the normalized transmission rate under the constraints of minimizing the normalized transmitting power with the pre-defined bit error rate (BER). Simulations are carried out to verify the performance of both the traditional genetic algorithm and the adaptive genetic algorithm. Simulation results show that the convergence rates of the two algorithms increase significantly thanks to the initial population determined by the reduced-rules, without losing the accuracy of the decision-making. Meanwhile, the weight-independent objective function makes the algorithm more practical than the traditional methods.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.59-64
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• 2001

The robot soccer simulation game is a dynamic multi-agent environment. In this paper we suggest a new reinforcement learning approach to each agent's dynamic positioning in such dynamic environment. Reinforcement learning is the machine learning in which an agent learns from indirect, delayed reward an optimal policy to chose sequences of actions that produce the greatest cumulative reward. Therefore the reinforcement learning is different from supervised learning in the sense that there is no presentation of input pairs as training examples. Furthermore, model-free reinforcement learning algorithms like Q-learning do not require defining or learning any models of the surrounding environment. Nevertheless it can learn the optimal policy if the agent can visit every state- action pair infinitely. However, the biggest problem of monolithic reinforcement learning is that its straightforward applications do not successfully scale up to more complex environments due to the intractable large space of states. In order to address this problem. we suggest Adaptive Mediation-based Modular Q-Learning (AMMQL)as an improvement of the existing Modular Q-Learning (MQL). While simple modular Q-learning combines the results from each learning module in a fixed way, AMMQL combines them in a more flexible way by assigning different weight to each module according to its contribution to rewards. Therefore in addition to resolving the problem of large state effectively, AMMQL can show higher adaptability to environmental changes than pure MQL. This paper introduces the concept of AMMQL and presents details of its application into dynamic positioning of robot soccer agents.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.173-177
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• 2009

With the advent of light-weight daily physiological signal monitoring sensors, intelligent inference and analysis method for physiological signal monitoring application, commercialized products and services are released. However, practical constraints still remain for daily physiological signal monitoring. Most devices provide rough health check function and analyze with randomly sampled measurements. In this work, we propose the probabilistic modeling of physiological signal analysis. This model represent the relationship between previous user measurement (history), other group`s type, model and current observation. From the experiment, we found that the personalized analysis with long term regular data shows reliable result and reduces the analyzing errors. In addition, participants agree that the personalized analysis shows reliable and adaptive information than other standard analysis method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.132-137
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• 2003

This performance is motivated to develop a tracking antenna system for receive the satellite broadcasting signal in the coast sailing ship. Therefore, this system is made to small size, light weight and simple operation which is must to low cost system for popularization of small size ship and adaptive possibilities with useful on a ship in the coast using 1 axis Az-mount. The antenna mount structure is a compact size and easy operation to the Az-axis type which is operated by step motor. The antenna unit is a domestic made plate type of patch array and ship's moving detection is using the gyro sensor for ship's moving control. We are designed to algorithm, which walking is abreast for step track and ship's moving compensation. Ship's moving compensation is adapted to the closed loop control method by detection from gyro sensor. This system is consisted of micro processor, ADC, comparative amplifier, step motor driver, mount mechanism and algorithm. We have analysised the tracking performance of prototype on sailing ship board.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.3
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• pp.101-108
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• 2004

A FEM-based efficient method is developed for the shape optimization of 2-D structures. The combined SLP and Simplex method are coupled with finite element analysis. Selected set of master nodes on the design boundaries are employed as design variables and assigned to move towards their normal directions. The other nodes along the design boundaries are grouped into the master node. By interpolating the repositioned master nodes, the B-spline curves are formed so that the rest mid-nodes efficiently settle down on the B-spline curves. Mesh smoothing scheme is also applied for the nodes on the design boundary to maintain most finite elements in good quality. Finally, a numerical implementation of optimum design of an automobile torque converter piston subjected to pressure and centrifugal loads is presented. The results shows additional weight up to 13% may be saved after the shape optimization.

• The Journal of the Korea Contents Association
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• v.12 no.4
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• pp.31-39
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• 2012

DVC(Distributed Video Coding) techniques have been attracting a lot of research works since these enable us to implement the light-weight video encoder and to provide good coding efficiency by introducing the feedback channel. However, the feedback channel causes the decoder to increase the decoding complexity and requires very high decoding latency because of numerous iterative decoding processes. So, in order to reduce the decoding delay and then to implement in a real-time environment, this paper proposes several parity bit estimation methods which are based on the temporal correlation, spatial correlation and spatio-temporal correlations between LDPCA frames on each bit plane in the consecutive video frames in pixel-domain Wyner-Ziv video coding scheme and then the performances of these methods are compared in fast DVC scheme. Through computer simulations, it is shown that the adaptive spatio-temporal correlation-based estimation method and the temporal correlation-based estimation method outperform others for the video frames with the highly active contents and the low active contents, respectively. By using these results, the proposed estimation schemes will be able to be effectively used in a variety of different applications.

• Asian-Australasian Journal of Animal Sciences
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• v.22 no.3
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• pp.336-342
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• 2009

Avian embryos at high altitude are independent of maternal protection against hypoxia, which is contrary to mammals. It is well known that chronic hypoxic exposure at key points can significantly impact on avian development. Tibetan Chicken, a Chinese indigenous breed, living in Tibetan areas with an altitude of 2.2 to 4.1 thousand meters, has an adaptive mechanism to hypoxia. In the present study, fertilized eggs of Tibetan Chicken were incubated under 13% and 21% oxygen concentration. Two lowland chicken breeds, Shouguang Chicken, an indigenous chicken breed in Shandong Province of China, and Dwarf Recessive White Chicken, an imported breed in Beijing, were used as control groups. The embryo mass and some organs such as brain, heart, liver, stomach and eye weight in the three species were measured at Hamburger-Hamilton stage 39, 41, 43 and 45 under hypoxic and normal conditions. The results showed that in hypoxia Tibetan Chicken significantly differed from the two lowland chicken breeds in embryo mass at Hamburger-Hamilton stage 41, 43 and 45 (p<0.01). In particular, Dwarf Recessive White Chicken and Shouguang Chicken showed retarded growth in hypoxic incubation (p<0.01), whereas Tibetan Chicken showed no significant difference between hypoxic and normal conditions (p>0.05). In addition, heart and the other organs showed different susceptibility to hypoxia at the studied stages. In conclusion, chronic hypoxia induced a change in the embryo development of the three different species and Tibetan Chicken showed adaptation to hypoxia. Of note, the embryo developmental physiology of Tibetan Chicken in response to hypoxia will shed light on the process of physiological acclimation or evolutionary adaptation as well as the study of clinical disease.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.11A
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• pp.1244-1252
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• 2004

In this paper, we derive some properties of linear detectors (zero forcing or minimum mean square error) at spatial multiplexing systems with alamouti's space-time block code. Based on the derived properies, this paper proposes low-complexity receivers. Implementing MMSE detector adaptively, the number of weight vectors to be calculated and updated is greatly reduced with the derived properties compared to the conventional methods. In the case of recursive least square algorithm, with the proposed approach computational complexity is reduced to less than the half. We also identify that sorted QR decomposition detector, which reduces the complexity of V-Blast detector, has the same properties for unitary matrix Q and upper triangular matrix R. A complexity reduction of about 50%, for sorted QR decomposition detector, can be achieved by using those properties without the loss of performance.