• Journal of the Institute of Electronics Engineers of Korea TC
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• v.37 no.1
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• pp.32-43
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• 2000

In this paper, we investigate the existing medium access control (MAC) protocols to integrate the voice and data services in packet-based CDMA networks and furthermore, propose a new approach to circumvent the operational limits inherent in them. We propose the $P^2R$-CDMA (Prioritized Packet Reservation Code Division Multiple Access) protocol for the uplink in the synchronous multi-code CDMA system, which employs the centralized frame-based slot reservation along with the dynamic slot assignment in the base station using the QoS-oriented dynamic priority of individual terminal. The simulation results show that, as compared with the existing scheme based on the adaptive permission probability control (APC), the proposed approach can significantly improve the system capacity while guaranteeing the real-time requirement of voice service.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.1
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• pp.52-60
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• 1997

In genetic algorithms(GA), a crossover is performed only at one or two places of a chromosome, and the fixed probabilities of crossover and mutation have been used during the entire generation. A GA with dynamic mutation is known to be superior to GAs with static mutation in performance, but so far no efficient dynamic mutation method has been presented. Accordingly in this paper, a GA is proposed to perform a uniform crossover based on the nucleotide(NU) concept, where DNA and RNA consist of NUs and also a concrete way to vary the probabilities of crossover and mutation dynamically for every generation is proposed. The efficacy of the proposed GA is demonstrated by its application to the unimodal, multimodal and nonlinear control problems, respectively. Simulation results show that in the convergence speed to the optimal value, the proposed GA was superior to existing ones, and the performance of GAs with varying probabilities of the crossover and the mutation improved as compared to GAs with fixed probabilities of the crossover and mutation. And it also shows that the NUs function as the building blocks and so the improvement of the proposed algorithm is supported by the building block hypothesis.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.3
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• pp.249-255
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• 2007

Under the situation of a fire, it is difficult for a rescue robot to use sensors such as vision sensor, ultrasonic sensor or laser distance sensor because of diffusion, refraction or block of light and sound by dense smoke. But, braille blocks that are installed for the visaully impaired at public places such as subway stations can be used as a map for autonomous mobile robot's localization and navigation. In this paper, we developed a laser sensor stan device which can detect braille blcoks in spite of dense smoke and integrated the device to the robot developed to carry out rescue mission in various hazardous disaster areas at KIST. We implemented MCL algorithm for robot's attitude estimation according to the scanned data and transformed a braille block map to a topological map and designed a nonlinear path tracking controller for autonomous navigation. From various simulations and experiments, we could verify that the developed laser sensor device and the proposed localization method are effective to autonomous tracking of braille blocks and the autonomous navigation robot system can be used for rescue under fire.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.513-519
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• 2013

The current vision-based approaches for emotion recognition, such as facial expression analysis, have many technical limitations in real circumstances, and are not suitable for applications that use them solely in practical environments. In this paper, we propose an approach for emotion recognition by combining extrinsic representations and intrinsic activities among the natural responses of humans which are given specific imuli for inducing emotional states. The intrinsic activities can be used to compensate the uncertainty of extrinsic representations of emotional states. This combination is done by using PRMs (Probabilistic Relational Models) which are extent version of bayesian networks and are learned by greedy-search algorithms and expectation-maximization algorithms. Previous research of facial expression-related extrinsic emotion features and physiological signal-based intrinsic emotion features are combined into the attributes of the PRMs in the emotion recognition domain. The maximum likelihood estimation with the given dependency structure and estimated parameter set is used to classify the label of the target emotional states.

• Journal of the Korean Institute of Telematics and Electronics
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• v.20 no.3
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• pp.61-68
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• 1983

In this paper various aspects of statistical maltiplexing of data signs have been investigated. A queueing model with finite waiting room and batch poisson arrivals is studied assuming that data signals are transmitted at a constant rate. Using traffic intensity and average burst length as parameters, overflow probabilities and expected queueing delay due to buffering are obtained. Also, a real system model of a statistical multiplexer that can be directly used in micro-programmed hardware realization is proposed. To examine the performance of the system, computer simulation has been done at various conditions. The results obtained can be used in designing a buffer efficiently.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8B
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• pp.780-786
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• 2002

In this paper several access schemes for voice and data packet over CPCH with waiting time signalling are proposed. Waiting time signalling is used for reducing the excessive attempt of UE when all the CPCH channel resources is being used by other UEs. The proposed schemes in this paper are better than other schemes in view of the voice/data packets? dropping probability, average access attempt to transmit voice/data packets successfully and the average throughput.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.4
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• pp.207-210
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• 2012

Genetic algorithms(GA) are well known and very popular stochastic optimization algorithm. Although, GA is very powerful method to find the global optimum, it has some drawbacks, for example, premature convergence to local optima, slow convergence speed to global optimum. To enhance the performance of GA, this paper proposes an adaptive partitioning-based genetic algorithm. The partitioning method, which enables GA to find a solution very effectively, adaptively divides the search space into promising sub-spaces to reduce the complexity of optimization. This partitioning method is more effective as the complexity of the search space is increasing. The validity of the proposed method is confirmed by applying it to several bench mark test function examples and the optimization of fuzzy controller for the control of an inverted pendulum.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.505-510
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• 2005

The RPO(randomized policy optimizer) algorithm, which utilizes probabilistic policy for the action selection, is a recently developed tool in the area of reinforcement learning, and has been shown to be very successful in several application problems. In this paper, we propose a modified RPO algorithm, whose critic network is adapted via RLS(Recursive Least Square) algorithm. In order to illustrate the applicability of the modified RPO method, we applied the modified algorithm to Kimura's robot and observed very good performance. We also developed a MATLAB-based animation program, by which the effectiveness of the training algorithms on the acceleration or the robot movement were observed.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.69-76
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• 2010

The segmentation of moving object in video sequence is a core technique of intelligent image processing system such as video surveillance, traffic monitoring and human tracking. A typical method to segment a moving region from the background is the background subtraction. The steps of background subtraction involve calculating a reference image, subtracting new frame from reference image and then thresholding the subtracted result. One of famous background modeling is Gaussian mixture model (GMM). Even though the method is known efficient and exact, GMM suffers from a problem that includes false pixels in ROI (region of interest), specifically shadow pixels. These false pixels cause fail of the post-processing tasks such as tracking and object recognition. This paper presents a method for removing false pixels included in ROT. First, we subdivide a ROI by using shape characteristics of detected objects. Then, a method is proposed to classify pixels from using histogram characteristic and comparing difference of energy that converts the color value of pixel into grayscale value, in order to estimate whether the pixels belong to moving object area or shadow area. The method is applied to real video sequence and the performance is verified.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.8
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• pp.1907-1914
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• 1998

This paper proposes the adaptive connection admission cotrol using the variale MRR(measurement reflection ratio) and the distribution of the number of cells arriving during the fixed interval. This distribution is estimated from the measured number of cells arriving at the output buffer during the fixed interval and traffic parameters specified by user. MRR is varied by the difference of estimated distribution and measurement distribution. As MRR is adaptively varied by estimated distribution error of accepted connections, it quickly reduces estimation error. Also, the scheduling scheme is proposed for multiplexed traffic with various traffic characteristics. For each traffic class, this scheme estimates adaptively equivalent bandwidth and schedules according to equivalent bandwidth ratio of each traffic class, so it improves cell loss rate and link utilization.