• Journal of Information Processing Systems
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• v.17 no.5
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• pp.879-891
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• 2021

With improvements in living conditions, an increasing number of people are choosing to spend their time traveling. Comfortable tour routes are affected by the season, time, and other local factors. In this paper, the influencing factors and principles of scenic spots are analyzed, a model used to find the available routes is built, and a multi-route choice model based on a game theory utilizing a path recommendation weight is developed. A Monte Carlo analysis of a tourist route subjected to fixed access point conditions is applied to account for uncertainties such as the season, start time, end time, stay time, number of scenic spots, destination, and start point. We use the Dijkstra method to obtain multiple path plans and calculate the path evaluation score using the Monte Carlo method. Finally, according to the user preference in the input path, game theory generates path ordering for user choice. The proposed approach achieves a state-of-the-art performance at the pseudo-imperial palace. Compared with other methods, the proposed method can avoid congestion and reduce the time cost.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.337-351
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• 2021

Automatically recognizing facial expressions in video sequences is a challenging task because there is little direct correlation between facial features and subjective emotions in video. To overcome the problem, a video facial expression recognition method using spatiotemporal recurrent neural network and feature fusion is proposed. Firstly, the video is preprocessed. Then, the double-layer cascade structure is used to detect a face in a video image. In addition, two deep convolutional neural networks are used to extract the time-domain and airspace facial features in the video. The spatial convolutional neural network is used to extract the spatial information features from each frame of the static expression images in the video. The temporal convolutional neural network is used to extract the dynamic information features from the optical flow information from multiple frames of expression images in the video. A multiplication fusion is performed with the spatiotemporal features learned by the two deep convolutional neural networks. Finally, the fused features are input to the support vector machine to realize the facial expression classification task. The experimental results on cNTERFACE, RML, and AFEW6.0 datasets show that the recognition rates obtained by the proposed method are as high as 88.67%, 70.32%, and 63.84%, respectively. Comparative experiments show that the proposed method obtains higher recognition accuracy than other recently reported methods.

• 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.31 no.5A
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• pp.493-500
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• 2006

This paper presents the efficient structure and parameter optimization of downlink beamforming transmitter in OFDMA/TDD system. To design downlink beamforming transmitter for multiple transmit antennas, an efficient beamforming structure for multiple users and the choice of word-length of each block are critical in the aspect of its performance and hardware complexity. We propose an efficient beamforming scheme, which stores the weights of subcarriers into memory without user identification at the receiver of base station and calculates the weights for corresponding user in a subcarrier unit of IFFT input at high speed. Also, we obtain the word-length of main data path and other design parameters by fixed-point simulation analysis. The proposed architecture could reduce the memory size proportional to the maximum number of users per frame, and the processing time of an OFDM symbol at the receiver of base station without the need of additional processing time for calculating the weights at the transmitter.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.5
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• pp.504-511
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• 2016

In this paper, MIMO system based on turbo equalization techniques which LDPC codes were outer code and space time trellis codes (STTC) were employed as an inner code are studied. LDPC decoder and STTC decoder are connected through the interleaving and de-interleaving that updates each other's information repeatedly. In conventional turbo equalization of MIMO system, BCJR decoder which decodes STTC coded bits required two-bit wise decoding processing. Therefore duo-binary turbo codes are optimal for MIMO system combined with STTC codes. However a LDPC decoder requires bit unit processing, because LDPC codes can't be applied to these system. Therefore this paper proposed turbo equalization for MIMO system based on LDPC codes combined with STTC codes. By the simulation results, we confirmed performance of proposed turbo equalization model was improved about 0.6dB than that of conventional LDPC codes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.3
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• pp.587-594
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• 2005

In the paper, after we propose a viterbi decoder which has multiple buffering and parallel processing decoding scheme through expanding time-divided imput signal, and map a FPGA, we implement a channel coding system together with PC-based software. Continuous input signal is buffered as order of decoding length and is parallel decoded using a high speed cell for viterbi decoding. Output data rate increases linearly with the cell formed the viterbi decoder, and flexible operation can be satisfied by programming controller and modifying input buffer. The tell for viterbi decoder consists of HD block for calculating hamming distance, CM block for calculating value in each state, TB block for trace-back operation, and LIFO. The implemented cell of viterbi decoder used 351 LAB(Logic Arrary Block) and stably operated in maximum 139MHz in APEX20KC EP20K600CB652-7 FPGA of ALTERA. The whole viterbi decoder including viterbi decoding cells, input/output buffers, and a controller occupied the hardware resource of $23\%$ and has the output data rate of 1Gbps.

• Journal of Satellite, Information and Communications
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• v.11 no.4
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• pp.58-62
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• 2016

In this paper, we propose a pre-processing scheme for improving indoor positioning accuracy in impulsive noise channel environments. The impulsive noise can be generated by multi-path fading effects by complicated indoor structures or interference environments, which causes an increase in demodulation error probability. The proposed pre-processing scheme is performed before a triangulation method to calculate user's position, and providing reliable input data demodulated from a received signal to the triangulation method. Therefore, we studied and proposed an adaptive threshold function for mitigation of the impulsive noise based on wavelet denoising. Through results of computer simulations for the proposed scheme, we confirmed that Bit Error Rate and Signal-to-Noise Ratio performance is improved compared to conventional schemes.

• Journal of the Korea Society of Computer and Information
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• v.13 no.2
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• pp.79-85
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• 2008

The middleware that provides RFID-based ubiquitous application service should process the data inputted constantly in real time, and acquire and deliver the answers of the questions in the application service. Studies for developing a Data Stream Management System(DSMS) has been performed in order to process a large amount of data stream inputted constantly in this way. Previous algorithms on data stream were mostly focused on reducing the average error between the answers of the successive questions and abandon the data according to the priority of them when a load occurs. This article is composed of presenting the necessity of the studies on the DSMS and speedy data processing, suggesting an algorithm to make Possible the speedy data processing using buffers and prompt questions and answers, and testing the performance of the data processing rate and whether a buffer is generated correspondingly to the algorithm suggested, in either a single or a multiple buffer, through simulations.

• The KIPS Transactions:PartA
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• v.18A no.1
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• pp.1-10
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• 2011

Physical modeling has been widely used for sound synthesis since it synthesizes high quality sound which is similar to real-sound for musical instruments. However, physical modeling requires a lot of parameters to synthesize a large number of sounds simultaneously for the musical instrument, preventing its real-time processing. To solve this problem, this paper proposes a single instruction, multiple data (SIMD) based multi-core processor that supports real-time processing of sound synthesis of gayageum which is a representative Korean traditional musical instrument. The proposed SIMD-base multi-core processor consists of 12 processing elements (PE) to control 12 strings of gayageum in which each PE supports modeling of the corresponding string. The proposed SIMD-based multi-core processor can generate synthesized sounds of 12 strings simultaneously after receiving excitation signals and parameters of each string as an input. Experimental results using a sampling reate 44.1 kHz and 16 bits quantization show that synthesis sound using the proposed multi-core processor was very similar to the original sound. In addition, the proposed multi-core processor outperforms commercial processors(TI's TMS320C6416, ARM926EJ-S, ARM1020E) in terms of execution time ($5.6{\sim}11.4{\times}$ better) and energy efficiency (about $553{\sim}1,424{\times}$ better).

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.279-285
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• 2007

The objective of the research is two fold. The first is to design and propose a stable and robust learning control algorithm. The controller is CMAC Learning Controller which consists of a model-based controller, such as LQR or PID, as a reference control and a CMAC. The second objective is to implement a reference control and CMAC at two different sampling rates. Generally, a conventional controller is designed based on a mathematical plant model. However, increasing complexity of the plant and accuracy requirement on mathematical models nearly prohibits the application of the conventional controller design approach. To avoid inherent complexity and unavoidable uncertainty in modeling, biology mimetic methods have been developed. One of such attempts is Cerebellar Model Articulation Computer(CMAC) developed by Albus. CMAC has two main disadvantages. The first disadvantage of CMAC is increasing memory requirement with increasing number of input variables and with increasing accuracy demand. The memory needs can be solved with cheap memories due to recent development of new memory technology. The second disadvantage is a demand for processing powers which could be an obstacle especially when CMAC should be implemented in real-time. To overcome the disadvantages of CMAC, we propose CMAC learning controller with multiple sampling rates. With this approach a conventional controller which is a reference to CMAC at high enough sampling rate but CMAC runs at the processor's unoccupied time. To show efficiency of the proposed method, an inverted pendulum controller is designed and implemented. We also demonstrate it's possibility as an industrial control solution and robustness against a modeling uncertainty.