• Water for future
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• v.28 no.1
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• pp.81-90
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• 1995

This study attempts to develop a stochastic system model for extension and prediction of monthly runoff series in river basins where the observed runoff data are insufficient although there are long-term hydrometeorological records. For this purpose, univariate models of a seasonal ARIMA type are derived from the time series analysis of monthly runoff, monthly precipitation and monthly evaporation data with trend and periodicity. Also, a causual model of multiple input-single output relationship that take monthly precipitation and monthly evaporation as input variables-monthly runoff as output variable is built by the cross-correlation analysis of each series. The performance of the univariate model and the multiple input-output model were examined through comparisons between the historical and the generated monthly runoff series. The results reveals that the multiple input-output model leads to the improved accuracy and wide range of applicability when extension and prediction of monthly runoff series is required.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.447-450
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• 2009

In this paper, binary pulse-antipodal modulation (2PAM) direct-sequence (DS) ultra-wideband (UWB) system is applied to multiple input multiple output (MIMO) system using vertical bell lab layered space-time (V-BLAST) structure to achieve high-data-rate communications over indoor wireless channels. The relationship between antenna dimension and BER performance of 2PAM DS UWB MIMO system is discussed. In the receiver of UWB-MIMO system, various MIMO detection algorithms such as zero-forcing (ZF), ZF-ordered successive interference cancellation (OSIC), minimum-mean-square-error (MMSE), MMSE-OSIC and maximum likelihood (ML) are comparatively studied.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.8
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• pp.1997-2004
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• 1994

A model analysis method has been developed in the paper. The method estimates the modal parameters of multiple input-output systems, assesses their quality, and seperates structural modes form computation ones. The modal parameter extraction algorithm is the least squares method with a finite difference model relating input and output time data. The quality of the estimated system model can be assessed in narrow frequency bands by comparing the measured and model predicted responses in time domain with the aid of digital filters. Structural modes can be effectively separated from computational ones using the convergence factor which represents the pole convergence rate. The modal analysis method has been applied to simulated and experimental vibration data to evaluate its utility and limitations.

• Journal of Korean Society for Quality Management
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• v.30 no.3
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• pp.186-194
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• 2002

In this paper we introduce formulae for estimating the failure rate of a large scaled software by using the Bayesian rule when a black-box random testing which selects an element(test case) at random with equally likely probability, is performed. A program or software can be treated as a mathematical function with a well-defined (input)domain and range. For a large scaled software, their input domains can be partitioned into multiple subdomains and exhaustive testing is not generally practical. Testing is proceeding with selecting a subdomain, and then picking a test case from within the selected subdomain. Whether or not the proportion of selecting one of the subdomains is assumed probability, we developed the formulae either case by using Bayesian rule with gamma distribution as a prior distribution.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.8
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• pp.851-858
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• 2009

In this study, we propose a new input device using vision technology for positioning of multiple DOFs. The input device is composed of multiple Tags on a transparent table and a vision camera below the table. Vision camera detects LEDs at the bottom of each Tag to derive information of the ID, position and orientation. The information are used to determine position and orientation of remote target DOFs. Our developed approach is very reliable and effective, especially when the corresponding DOFs are from many independent individuals. We show an application example with a SCARA robot to prove the flexibility and extendability.

• Journal of information and communication convergence engineering
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• v.8 no.5
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• pp.498-501
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• 2010

In this paper, we extend ultra-wideband (UWB) single input single output (SISO) systems with a hybrid pulse amplitude and position modulation (PAPM) to single input multiple output (SIMO) systems using receive antenna diversity. The performance of a rake receive diversity combining scheme for UWB SIMO systems with a PAPM is examined in a log-normal multipath fading channel and also compared with that of a time-switched transmit diversity (TSTD) multiple input single output (MISO) system. It is seen that as the number of receive antennas increases, the receive diversity combining system improves the error performance. It is shown that the TSTD UWB MISO systems offer the performance equivalent to the receive diversity combining scheme for SIMO systems.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.6
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• pp.444-451
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• 2017

In this paper, we have evaluated and analyzed OTFS(Orthogonal Time Frequency Space) modulation and OTFS-MIMO(Multiple Input Multiple Output) system. OTFS modulation can concisely compensate delay-Doppler spreading effect by using 2D(2-Dimension) iDFT (inverse Discrete Fourier Transform) and DFT(Discrete Fourier Transform) operation. It enables OTFS system to transmit high-speed data. Especially, OTFS-MIMO system can transmit all data streams without performance degradation on high Doppler frequency channel. As simulation results, we have confirmed that $1{\times}1$ OTFS system's achievable rate is a similar to each stream of $2{\times}2$ OTFS-MIMO system. That is, we have also confirmed that $2{\times}2$ MIMO system can completely achieve double achievable rate in comparison with OTFS system on high Doppler frequency channel.

• Korean Journal of Computational Design and Engineering
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• v.2 no.2
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• pp.77-84
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• 1997

This paper is concerning the development of multiple neural networks system of problem domains where the complete input space can be decomposed into several different regions, and these are known prior to training neural networks. We will adopt oblique decision tree to represent the divided input space and sel ect an appropriate subnetworks, each of which is trained over a different region of input space. The overall architecture of multiple neural networks system, called the federated architecture, consists of a facilitator, normal subnetworks, and tile networks. The role of a facilitator is to choose the subnetwork that is suitable for the given input data using information obtained from decision tree. However, if input data is close enough to the boundaries of regions, there is a large possibility of selecting the invalid subnetwork due to the incorrect prediction of decision tree. When such a situation is encountered, the facilitator selects a tile network that is trained closely to the boundaries of partitioned input space, instead of a normal subnetwork. In this way, it is possible to reduce the large error of neural networks at zones close to borders of regions. The validation of our approach is examined and verified by applying the federated neural networks system to the configuration design of a midship structure.

• ETRI Journal
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• v.42 no.3
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• pp.341-350
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• 2020

In a wireless sensor network (WSN), the data transmission technique based on the cooperative multiple-input multiple-output (CMIMO) scheme reduces the energy consumption of sensor nodes quite effectively by utilizing the space-time block coding scheme. However, in networks with high node density, the scheme is ineffective due to the high degree of correlated data. Therefore, to enhance the energy efficiency in high node density WSNs, we implemented the distributed source coding (DSC) with the virtual multiple-input multiple-output (MIMO) data transmission technique in the WSNs. The DSC-MIMO first compresses redundant source data using the DSC and then sends it to a virtual MIMO link. The results reveal that, in the DSC-MIMO scheme, energy consumption is lower than that in the CMIMO technique; it is also lower in the DSC single-input single-output (SISO) scheme, compared to that in the SISO technique at various code rates, compression rates, and training overhead factors. The results also indicate that the energy consumption per bit is directly proportional to the velocity and training overhead factor in all the energy saving schemes.

• Journal of Information Processing Systems
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• v.9 no.3
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• pp.499-510
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• 2013

Hardware-Software co-simulation of a multiple image encryption technique shall be described in this paper. Our proposed multiple image encryption technique is based on the Latin Square Image Cipher (LSIC). First, a carrier image that is based on the Latin Square is generated by using 256-bits of length key. The XOR operation is applied between an input image and the Latin Square Image to generate an encrypted image. Then, the XOR operation is applied between the encrypted image and the second input image to encrypt the second image. This process is continues until the nth input image is encrypted. We achieved hardware co-simulation of the proposed multiple image encryption technique by using the Xilinx System Generator (XSG). This encryption technique is modeled using Simulink and XSG Block set and synthesized onto Virtex 2 pro FPGA device. We validated our proposed technique by using the hardware software co-simulation method.