• Journal of Information Processing Systems
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• v.17 no.3
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• pp.556-570
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• 2021

The existing video expression recognition methods mainly focus on the spatial feature extraction of video expression images, but tend to ignore the dynamic features of video sequences. To solve this problem, a multi-mode convolution neural network method is proposed to effectively improve the performance of facial expression recognition in video. Firstly, OpenFace 2.0 is used to detect face images in video, and two deep convolution neural networks are used to extract spatiotemporal expression features. Furthermore, spatial convolution neural network is used to extract the spatial information features of each static expression image, and the dynamic information feature is extracted from the optical flow information of multiple expression images based on temporal convolution neural network. Then, the spatiotemporal features learned by the two deep convolution neural networks are fused by multiplication. Finally, the fused features are input into support vector machine to realize the facial expression classification. Experimental results show that the recognition accuracy of the proposed method can reach 64.57% and 60.89%, respectively on RML and Baum-ls datasets. It is better than that of other contrast methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.183-186
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• 2015

Recently, the demand for the safety and the information delivery system in the ship increases. The deployment of the wireless sensor networks instead of using the built-in wired networks or the setup of the new wired networks is more desirable than the deployment of the wired networks in a ship after its final production since it can reduce the cost and the time of the brand new wired networks by deforming some of the internal structure of the ship. In this paper, the shipboard signal propagation measurement system based on the signature sequence-two way slave mode are designed and its measurement data are analysed after measuring the signal propagation characteristics. Consequently, it is expected that the reliable and cost-effective signal measurement system for the deployment of the shipboard wireless networks can be built.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.19 no.2 s.72
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• pp.125-138
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• 2006

The use of system identification approaches for damage detection has been expanded in recent years owing to the advancements in data acquisition system andinformation processing techniques. Soft computing techniques such as neural networks and genetic algorithm have been utilized increasingly for this end due to their excellent pattern recognition capability. In this study, damage detection of bridge structures using neural networks technique based on the modal properties is presented, which can effectively consider the modeling uncertainty in the analysis model from which the training patterns are to be generated. The differences or the ratios of the mode shape components between before and after damage are used as the input to the neural networks in this method, since they are found to be less sensitive to the modeling errors than the mode shapes themselves. Two numerical example analyses on a simple beam and a multi-girder bridge are presented to demonstrate the effectiveness and applicability of the proposed method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.4
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• pp.24-33
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• 2004

In this paper, the helicopter flight control system using online adaptive neural networks which have the universal function approximation property is considered. It is not compensation for modeling errors but approximation two functions required for feedback linearization control action from input/output of the system. To guarantee the tracking performance and the stability of the closed loop system replaced two nonlinear functions by two neural networks, weight update laws are provided by Lyapunov function and the simulation results in low speed flight mode verified the performance of the control system with the neural networks.

• The KIPS Transactions:PartD
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• v.15D no.1
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• pp.131-138
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• 2008

This paper describes the implementations of the first application service based on embedded Linux; Mobile Teller which uses WiBro network for data communications and CDMA network for voice communications. Currently, with the appearance of WiBro service, dual-mode terminals which support two heterogeneous networks are available. But, the development of applications which effectively use these networks for providing better service to user is rarely prepared. At Mobile Teller, when a sender on a dual-mode terminal types texts, the texts are transmitted to a TTS server located in the Internet through WiBro network. Subsequently, the TTS server converts the texts into voices and transmits the voice data to the dual-mode terminal. At last the dual-mode terminal sends the voice to the receiver through the CDMA network. In case of noisy environment or when a user has difficulty in speaking, Mobile Teller makes voice communication possible

• Journal of Sensor Science and Technology
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• v.22 no.1
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• pp.18-27
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• 2013

Real-time monitoring is one of the prime necessities in a weapon flight test that is required for the efficient and timely collection of large amounts of high-rate sampled data acquired by an event-trigger. The wireless sensor network is a good candidate to resolve this requirement, especially considering the inhospitable environment of a weapon flight test. In this paper, we propose a priority based multi-channel MAC protocol with CSMA/CA over a single radio for a real-time monitoring of a weapon flight test. Multi-channel transmissions of nodes can improve the network performance in wireless sensor networks. Our proposed MAC protocol has two operation modes: Normal mode and Priority Mode. In the normal mode, the node exploits the normal CSMA/CA mechanism. In the priority mode, the node has one of three grades - Class A, B, and C. The node uses a different CSMA/CA mechanism according to its grade that is determined by a signal level. High grade nodes can exploit more channels and lower backoff exponents than low ones, which allow high grade nodes to obtain more transmission opportunities. In addition, it can guarantee successful transmission of important data generated by high grade nodes. Simulation results show that the proposed MAC exhibits excellent performance in an event-triggered real-time application.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.1996-2013
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• 2015

This paper considers a scenario that more D2D users exist in the cell, they compete for cellular resources to increase their own data rates, which may cause transmission interference to cellular users (CU) and the unfairness of resource allocation. We design a resource allocation scheme for selfish D2D users assisted by cooperative relay technique which is used to further enhance the users' transmission rates, meanwhile guarantee the QoS requirement of the CUs. Two transmission modes are considered for D2D users: direct transmission mode and cooperative relay transmission mode, both of which reuses the cellular uplink frequency resources. To ensure the fairness of resource distribution, Nash bargaining theory is used to determine the transmission mode and solve the bandwidth allocation problem for D2D users choosing cooperative relay transmission mode, and coalition formation game theory is used to solve the uplink frequency sharing problem between D2D users and CUs through a new defined "Selfish order". Through theoretical analysis, we obtain the closed Nash bargaining solution under CUs' rate constraints, and prove the stability of the formatted coalition. Simulation results show that the proposed resource allocation approach achieves better performance on resource allocation fairness, with only little sacrifice on the system sum rates.

• Journal of Industrial Technology
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• v.32 no.A
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• pp.3-8
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• 2012

In IEEE 802.16j standard document, two modes about usage of RS are proposed; one is transparent mode to enhance data throughput and the other is non-transparent mode to extend coverage. In this paper, we focus on non-transparent mode and find that the mode also affects data throughput. We analyze data throughput on various RS topology and their extended coverage area in non-transparent mode. From the analysis, we see that higher throughput can be obtained when MR-BS and RS are located distantly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4291-4310
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• 2015

This paper investigates the traffic offloading over unlicensed bands for two-tier multi-mode small cell networks. We formulate this problem as a Stackelberg game and apply a hierarchical learning framework to jointly maximize the utilities of both macro base station (MBS) and small base stations (SBSs). During the learning process, the MBS behaves as a leader and the SBSs are followers. A pricing mechanism is adopt by MBS and the price information is broadcasted to all SBSs by MBS firstly, then each SBS competes with other SBSs and takes its best response strategies to appropriately allocate the traffic load in licensed and unlicensed band in the sequel, taking the traffic flow payment charged by MBS into consideration. Then, we present a hierarchical Q-learning algorithm (HQL) to discover the Stackelberg equilibrium. Additionally, if some extra information can be obtained via feedback, we propose an improved hierarchical Q-learning algorithm (IHQL) to speed up the SBSs' learning process. Last but not the least, the convergence performance of the proposed two algorithms is analyzed. Numerical experiments are presented to validate the proposed schemes and show the effectiveness.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.721-724
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• 1994

This paper proposes a continuous hitting by a flexible link hammer. This hammer system is used only the first mode of vibration for a desired hitting. The input of the hammer driver for a continuous hitting is obtained from numerical solutions of two sets of non-linear simultaneous equations which satisfy the hitting conditions. Being too complicated, these numerical calculations are not useful for online processing. Therefore, the multi-layered neural networks are applied to the generation of the input patterns of the hammer driver. The trained network outputs agree well to the numerical solutions.