• Proceedings of the IEEK Conference
• /
• 2002.07b
• /
• pp.1252-1255
• /
• 2002

In this paper, face recognition algorithm, by using skin color information of HSI color coordinate collected from face images, elliptical mask, fratures of face including eyes, nose and mouth, and geometrical feature vectors of face and facial angles, is proposed. The proposed algorithm improved face region extraction efficacy by using HSI information relatively similar to human's visual system along with color tone information about skin colors of face, elliptical mask and intensity information. Moreover, it improved face recognition efficacy with using feature information of eyes, nose and mouth, and Θ1(ACRED), Θ2(AMRED) and Θ 3(ANRED), which are geometrical face angles of face. In the proposed algorithm, it enables exact face reading by using color tone information, elliptical mask, brightness information and structural characteristic angle together, not like using only brightness information in existing algorithm. Moreover, it uses structural related value of characteristics and certain vectors together for the recognition method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.10
• /
• pp.2509-2528
• /
• 2012

Time division multiple access (TDMA) is a widely used media access control (MAC) technique that can provide collision-free and reliable communications, save energy and bound the delay of packets. In TDMA, energy saving is usually achieved by switching the nodes' radio off when such nodes are not engaged. However, the frequent switching of the radio's state not only wastes energy, but also increases end-to-end delay. To achieve high energy efficiency and low delay, as well as to further minimize the number of time slots, a multi-objective TDMA scheduling problem for industrial wireless mesh networks is presented. A hybrid algorithm that combines genetic algorithm (GA) and simulated annealing (SA) algorithm is then proposed to solve the TDMA scheduling problem effectively. A number of critical techniques are also adopted to reduce energy consumption and to shorten end-to-end delay further. Simulation results with different kinds of networks demonstrate that the proposed algorithm outperforms traditional scheduling algorithms in terms of addressing the problems of energy consumption and end-to-end delay, thus satisfying the demands of industrial wireless mesh networks.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.831-833
• /
• 2004

In this paper, an obstacle avoidance algorithm is proposed for a network-based robot considering network delay by distribution. The proposed algorithm is based on the VFH(Vector Field Histogram) algorithm, and for the network-based robot system, in which it is assumed robot localization information is transmitted through network communication. In this paper, target vector for the VFH algorithm is estimated through the robot localization information and the measurement of its delay by distribution. The delay measurement is performed by time-stamp method. To synchronize all local clocks of the nodes distributed on the network, a global clock synchronization method is adopted. With the delay measurement, the robot localization estimation is performed by calculating the kinematics of the robot. The validation of the proposed algorithm is performed through the performance comparison of the obstacle avoidance between the proposed algorithm and the existing VFH algorithm on the network-based autonomous mobile robot.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.9
• /
• pp.4220-4241
• /
• 2017

For the downlink energy-harvesting small cell network, this paper proposes an interference management algorithm based on distributed coalitional game. The cooperative interference management problem of the energy-harvesting small cells is modeled as a coalitional game with transfer utility. Based on the energy harvesting strategy of the small cells, the time sharing mode of the small cells in the same coalition is determined, and an optimization model is constructed to maximize the total system rate of the energy-harvesting small cells. Using the distributed algorithm for coalition formation proposed in this paper, the stable coalition structure, optimal time sharing strategy and optimal power distribution are found to maximize the total utility of the small cell system. The performance of the proposed algorithm is discussed and analyzed finally, and it is proved that this algorithm can converge to a stable coalition structure with reasonable complexity. The simulations show that the total system rate of the proposed algorithm is superior to that of the non-cooperative algorithm in the case of dense deployment of small cells, and the proposed algorithm can converge quickly.

• ETRI Journal
• /
• v.42 no.6
• /
• pp.922-931
• /
• 2020

A hierarchical iterative algorithm for the canonical polyadic decomposition (CPD) of tensors is proposed by improving the traditional conjugate gradient least squares (CGLS) method. Methods based on algebraic operations are investigated with the objective of estimating the direction of arrival (DoA) and polarization parameters of signals impinging on an array with electromagnetic (EM) vector-sensors. The proposed algorithm adopts a hierarchical iterative strategy, which enables the algorithm to obtain a fast recovery for the highly collinear factor matrix. Moreover, considering the same accuracy threshold, the proposed algorithm can achieve faster convergence compared with the alternating least squares (ALS) algorithm wherein the highly collinear factor matrix is absent. The results reveal that the proposed algorithm can achieve better performance under the condition of fewer snapshots, compared with the ALS-based algorithm and the algorithm based on generalized eigenvalue decomposition (GEVD). Furthermore, with regard to an array with a small number of sensors, the observed advantage in estimating the DoA and polarization parameters of the signal is notable.

• Proceedings of the IEEK Conference
• /
• 2007.07a
• /
• pp.315-316
• /
• 2007

This paper presents a tracking algorithm, which is insensitive to light conditions. The proposed algorithm uses the depth information as well as the intensity information to track objects reliably. Specifically we use a disparity map to detect an object and employ the intensity histogram to track the motion of the object. Simulation results demonstrate the performance of the proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.12
• /
• pp.2326-2339
• /
• 2011

To reduce the implementation complexity of the Vertical Bell Labs layered space-time (V-BLAST) systems with respect to the zero-forcing (ZF) criterion, a computationally efficient recursive algorithm is proposed. A fast implementation of the proposed algorithm is developed and its complexity is analyzed in detail. The proposed algorithm matches the ZF-OSIC detection well, and its three significant advantages can be demonstrated by analyses and simulations. Firstly, its speedups over the conventional ZF-OSIC with norm-based ordering, the original fast recursive algorithm (FRA) and the fastest known algorithm (FKA) in the number of flops are 1.58, 2.33 and 1.22, respectively. Secondly, a much simpler implementation than FRA and FKA can be expected. Finally, the storage requirements are lower than those of FRA and FKA. These advantages make the proposed algorithm more efficient and practical.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.64 no.10
• /
• pp.1418-1425
• /
• 2015

In this paper, an filtering method of FI(Fault Indication) information generated by FRTU(Feeder Remote Terminal Unit)s is proposed for the present DAS(Distribution Automation System). In order to find fault area, correct FI information should be generated. But when a single line-to-ground fault occurs, FI information is generated in downside of the fault in some circumstance because existing FI algorithm considers only magnitude. These wrong FI information can be removed by changing existing algorithm. An improved algorithm considers both the direction of zero-sequence current and the phase of three-phase current&voltage. But many FRTUs are distributed in DAS and Changing the algorithm all of FRTU will spend a lot of time and cost. On the other hand, an filtering algorithm proposed in this paper can substitute for it. The filtering algorithm also considers both the direction of zero-sequence current and the phase of three-phase current&voltage. In case study, the proposed method has been shown the reasonability in filtering the fault indication information.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.12
• /
• pp.4567-4583
• /
• 2021

This study proposes an analytical approximation algorithm based on extreme value theory (EVT) for the inverse of the power of the incomplete Gamma function. First, the Gumbel function is used to approximate the power of the incomplete Gamma function, and the corresponding inverse problem is transformed into the inversion of an exponential function. Then, using the tail equivalence theorem, the normalized coefficient of the general Weibull distribution function is employed to replace the normalized coefficient of the random variable following a Gamma distribution, and the approximate closed form solution is obtained. The effects of equation parameters on the algorithm performance are evaluated through simulation analysis under various conditions, and the performance of this algorithm is compared to those of the Newton iterative algorithm and other existing approximate analytical algorithms. The proposed algorithm exhibits good approximation performance under appropriate parameter settings. Finally, the performance of this method is evaluated by calculating the thresholds of space-time block coding and space-frequency block coding pattern recognition in multiple-input and multiple-output orthogonal frequency division multiplexing. The analytical approximation method can be applied to other related situations involving the maximum statistics of independent and identically distributed random variables following Gamma distributions.

• International Journal of Internet, Broadcasting and Communication
• /
• v.15 no.3
• /
• pp.176-184
• /
• 2023

Points of interest (POIs) are widely used in tourism recommendations and to provide information about areas of interest. Currently, situation judgement using POI and GPS data is mainly rule-based. However, this approach has the limitation that inferences can only be made using predefined POI information. In this study, we propose an algorithm that uses POI data, GPS data, and schedule information to calculate the current speed, location, schedule matching, movement trajectory, and POI coverage, and uses machine learning to determine whether to stay or go. Based on the input data, the clustered information is labelled by k-means algorithm as unsupervised learning. This result is trained as the input vector of the SVM model to calculate the probability of moving and staying. Therefore, in this study, we implemented an algorithm that can adjust the schedule using the travel schedule, POI data, and GPS information. The results show that the algorithm does not rely on predefined information, but can make judgements using GPS data and POI data in real time, which is more flexible and reliable than traditional rule-based approaches. Therefore, this study can optimize tourism scheduling. Therefore, the stay detection algorithm using GPS movement trajectories and POIs developed in this study provides important information for tourism schedule planning and is expected to provide much value for tourism services.