• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.2
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• pp.122-129
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• 1988

A design method of decentralized state observer for large scale interconnected systems is proposed by the use of interconnection rejection approach and interconnection modelling technique. The proposed design method is developed based on the interconnection partitioning. Therefore partitioning conditions are suggested. And the conditions for observer pole assignment and observer parameter determination procedures are described for possible interconnection patterns. The decentralized state observer gives good estimates without any information on the interconnection variables and estimations. In addition, a numerical example is given to explain the design procedures and to show the estimation performance of the decentralized observer.

• The Journal of Korea Robotics Society
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• v.3 no.1
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• pp.23-32
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• 2008

This paper presents a task planning system for a steward robot, which has been developed as an interactive intermediate agent between an end-user and a complex smart home environment called the ISH (Intelligent Sweet Home) at KAIST (Korea Advanced Institute of Science and Technology). The ISH is a large-scale robotic environment with various assistive robots and home appliances for independent living of the elderly and the people with disabilities. In particular, as an approach for achieving human-friendly human-robot interaction, we aim at 'simplification of task commands' by the user. In this sense, a task planning system has been proposed to generate a sequence of actions effectively for coordinating subtasks of the target subsystems from the given high-level task command. Basically, the task planning is performed under the framework of STRIPS (Stanford Research Institute Problem Solver) representation and the split planning method. In addition, we applied a state-partitioning technique to the backward split planning method to reduce computational time. By analyzing the obtained graph, the planning system decomposes an original planning problem into several independent sub-problems, and then, the planning system generates a proper sequence of actions. To show the effectiveness of the proposed system, we deal with a scenario of a planning problem in the ISH.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.1
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• pp.9-15
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• 2021

Recently, it is increasingly necessary to run high-end neural network applications with huge computation overhead on top of resource-constrained embedded systems, such as wearable devices. While the huge computational overhead can be alleviated by distributed neural networks running on multiple separate devices, existing distributed neural network techniques suffer from a large traffic between the devices; thus are very vulnerable to communication failures. These drawbacks make the distributed neural network techniques inapplicable to wearable devices, which are connected with each other through unstable and low data rate communication medium like human body communication. Therefore, in this paper, we propose a distributed neural network partitioning technique that is resilient to communication failures. Furthermore, we show that the proposed technique also improves the inference accuracy even in case of no communication failure, thanks to the improved network partitioning. We verify through comparative experiments with a real-life neural network application that the proposed technique outperforms the existing state-of-the-art distributed neural network technique in terms of accuracy and resiliency to communication failures.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.8
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• pp.2003-2012
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• 1996

The 16- and 32-state Trellis-coded M-ary 4-dimensional (4-D) orthogonal modulation scheme with a frequency-reuse technique have been investigated. Here, 5 coded bits form a rate 4/5 convolutional encoder provide 32 possible symbols. Then the signals are mapped by a M-ary 4-D orthogonal modulator, where each signal has equal energy and is PSK modulated. In the M-ary 4-D modulator, we have employed the vectors which is derived by the optimization technique of signal waveforms in a 4-D sphere. This technique is usedin maximizing the minimum Euclidean distance between a set of signal poits on a multidimensional sphere. By combinig trellis coding with M-ary 4-D modulation and proper set-partitioning, we have obtained a considerable impeovement in the free minimum distance of the system over an AWGN channel. The 16-state scheme obtains coding gains up to 5.5 dB over the uncoded two-independent QPSK scheme and 2.5 dB over the two-independent 2-D TCM scheme. And, the 32-state scheme obtains coding gains up to 6.4 dB over the uncoded two-independent QPSK schemeand 3.4 dB over the two-independent 2-D TCM scheme.

• Journal of Korean Society on Water Environment
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• v.36 no.5
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• pp.353-363
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• 2020

Hydrologic models can be classified into two types: those for understanding physical processes and those for predicting hydrologic quantities. This study deals with how to use the model to predict today's stream flow based on the system's knowledge of yesterday's state and the model parameters. In this regard, for the model to generate accurate predictions, the uncertainty of the parameters and appropriate estimates of the state variables are required. In this study, a relatively simple hydrologic partitioning model is proposed that can explicitly implement the hydrologic partitioning process, and the posterior distribution of the parameters of the proposed model is estimated using the Markov chain Monte Carlo approach. Further, the application method of the ensemble Kalman filter is proposed for updating the normalized soil moisture, which is the state variable of the model, by linking the information on the posterior distribution of the parameters and by assimilating the observed steam flow data. The stochastically and recursively estimated stream flows using the data assimilation technique revealed better representation of the observed data than the stream flows predicted using the deterministic model. Therefore, the ensemble Kalman filter in conjunction with the Markov chain Monte Carlo approach could be a reliable and effective method for forecasting daily stream flow, and it could also be a suitable method for routinely updating and monitoring the watershed-averaged soil moisture.

• Smart Structures and Systems
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• v.14 no.6
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• pp.1221-1245
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• 2014

Real-time hybrid simulation (RTHS) is a promising cyber-physical technique used in the experimental evaluation of civil infrastructure systems subject to dynamic loading. In RTHS, the response of a structural system is simulated by partitioning it into physical and numerical substructures, and coupling at the interface is achieved by enforcing equilibrium and compatibility in real-time. The choice of partitioning parameters will influence the overall success of the experiment. In addition, due to the dynamics of the transfer system, communication and computation delays, the feedback force signals are dependent on the system state subject to delay. Thus, the transfer system dynamics must be accommodated by appropriate actuator controllers. In light of this, guidelines should be established to facilitate successful RTHS and clearly specify: (i) the minimum requirements of the transfer system control, (ii) the minimum required sampling frequency, and (iii) the most effective ways to stabilize an unstable simulation due to the limitations of the available transfer system. The objective of this paper is to establish a stability switch criterion due to systematic experimental errors. The RTHS stability switch criterion will provide a basis for the partitioning and design of successful RTHS.

• Geomechanics and Engineering
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• v.33 no.1
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• pp.11-18
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• 2023

This study explores a new energy partitioning approach to determine the fracture toughness of 3-D printed pristine/recycled high density polyethylene (HDPE) blends employing the essential work of fracture (EWF) concept. The traditional EWF approach conducts a uniaxial tensile test with double-edge notched tensile (DENT) specimens and measures the total energy defined by the area under a load-displacement curve until failure. The approach assumes that the entire total energy contributes to the fracture process only. This assumption is generally true for extruded polymers that fracture occurs in a material body. In contrast to the traditional extrusion manufacturing process, the current 3-D printing technique employs fused deposition modeling (FDM) that produces layer-by-layer structured specimens. This type of specimen tends to include separation energy even after the complete failure of specimens when the fracture test is conducted. The separation is not relevant to the fracture process, and the raw experimental data are likely to possess random variation or noise during fracture testing. Therefore, the current EWF approach may not be suitable for the fracture characterization of 3-D printed specimens. This paper proposed a new energy partitioning approach to exclude the irrelevant energy of the specimens caused by their intrinsic structural issues. The approach determined the energy partitioning location based on experimental data and observations. Results prove that the new approach provided more consistent results with a higher coefficient of correlation.

• Korean Journal of Remote Sensing
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• v.1 no.1
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• pp.5-27
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• 1985

A hill-sliding technique was devised to extract Gaussian clusters from the multivariate probability density estimates of sample data for the first step of iterative unsupervised classification. The underlying assumption in this approach was that each cluster possessed a unimodal normal distribution. The key idea was that a clustering function proposed could distinguish elements of a cluster under formation from the rest in the feature space. Initial clusters were extracted one by one according to the hill-sliding tactics. A dimensionless cluster compactness parameter was proposed as a universal measure of cluster goodness and used satisfactorily in test runs with Landsat multispectral scanner (MSS) data. The normalized divergence, defined by the cluster divergence divided by the entropy of the entire sample data, was utilized as a general separability measure between clusters. An overall clustering objective function was set forth in terms of cluster covariance matrices, from which the cluster compactness measure could be deduced. Minimal improvement of initial data partitioning was evaluated by this objective function in eliminating scattered sparse data points. The hill-sliding clustering technique developed herein has the potential applicability to decomposition of any multivariate mixture distribution into a number of unimodal distributions when an appropriate diatribution function to the data set is employed.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.72-74
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• 2000

This paper presents the linear model of the measurement system with Phasor Measurement Units (PMU's) and the parallel processing technique to determinate state vectors of a power system. The conventional model of the PMU measurement system is in a dilemma that it is not applicable to optimal PMU placements and it needs more PMU to apply this model. In order to improve this defect, in this paper, the extended linear model which adaptable to optimal PMU placements considering the feature of zero injection bus is proposed. Because the proposed model is expressed as over-determined measurement equation, the efficient algorithm is needed. This paper proposed the partitioning scheme and the process algorithm for parallel determinating state vectors of a power system efficiently. The performance of the proposed linear model and the parallel processing algorithm is evaluated with IEEE sample systems.

• The Journal of Information Technology
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• v.5 no.1
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• pp.133-142
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• 2002

This paper presents an efficient implementation of the linear window operator. I derived computational primitives based upon a block state space representation. The computational primitive can be implemented as a data path for a programmable processor, which can be used for the efficient implementation of a linear window operator. A multiprocessor architecture is presented for the realtime processing of a linear window operator. The architecture is designed based upon the data partitioning technique. Performance analysis for the various block size is provided.