• Journal of Korean Institute of Industrial Engineers
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• v.21 no.4
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• pp.581-591
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• 1995

The main objective of this study is to compare three representative methods predicting compressive forces on lumbosacral disc : LP-based method, double LP-based method and EMG-assisted method. Two subjects simulated lifting tasks performed in the refractories industry, in which vertical and horizontal distance, and weight of load were varied. To calculate the L5/S1 compressive forces, EMG signals from six trunk muscles were measured and postural data and locations of load were recorded using the Motion Analysis System. The EMG-assisted model was shown to reflect well all three factors considered here. On the other hand, the compressive forces of the LP-based model and the double LP-based model were only significantly affected by weight of load. In addition, lowly positive correlation was observed between compressive forces of the EMG-assisted model and lifting index(LI) of 1991 NIOSH lifting equation. From this results, it can be concluded that compressive forces on L5/S1 by the EMG-assisted method should be used as biomechanical criterion in order to evaluate risk of jobs precisely, and LI can not evaluate risk of lifting tasks fully.

• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.437-442
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• 2005

For the purpose of speaker normalization in speaker independent speech recognition systems, experiments are conducted on a method based on Gaussian mixture model(GMM). The method, which is an improvement of the previous study based on vector quantizer, consists of modeling the probability distribution of canonical feature vectors by a GMM with an appropriate number of clusters, and of estimating the warp factor of a test speaker by making use of the obtained probabilistic model. The purpose of this study is twofold: improving the existing ML based methods, and comparing the performance of what is called 'soft decision' method with that of the previous study based on vector quantizer. The effectiveness of the proposed method is investigated by recognition experiments on the TIMIT corpus. The experimental results showed that a little improvement could be obtained tv adjusting the number of clusters in GMM appropriately.

• International Journal of Concrete Structures and Materials
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• v.9 no.2
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• pp.255-266
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• 2015

A strut-and-tie based method intended for determining the load-carrying capacity of reinforced concrete (RC) corbels is presented in this paper. In addition to the normal strut-and-tie force equilibrium requirements, the proposed model is based on secant stiffness formulation, incorporating strain compatibility and constitutive laws of cracked RC. The proposed method evaluates the load-carrying capacity as limited by the failure modes associated with nodal crushing, yielding of the longitudinal principal reinforcement, as well as crushing or splitting of the diagonal strut. Load-carrying capacity predictions obtained from the proposed analysis method are in a better agreement with corbel test results of a comprehensive database, comprising 455 test results, compiled from the available literature, than other existing models for corbels. This method is illustrated to provide more accurate estimates of behaviour and capacity than the shear-friction based approach implemented by the ACI 318-11, the strut-and-tie provisions in different codes (American, Australian, Canadian, Eurocode and New Zealand).

• The Transactions of the Korea Information Processing Society
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• v.6 no.11S
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• pp.3399-3409
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• 1999

Information filtering for internet search, in which new information retrieval environment is given, is different from traditional methods such as bibliography information filtering, news-group and E-mail filtering. Therefore, we cannot expect high performance from the traditional information filtering models when they are applied to the new environment. To solve this problem, we inspect the characteristics of the new filtering environment, and propose a semantic-based filtering model which includes a new filtering method using WordNet. For extracting keywords from documents, this model uses the SDCC(Semantic Distance for Common Category) algorithm instead of the TF/IDF method usually used by traditional methods. The world sense ambiguation problem, which is one of causes dropping efficiency of internet search, is solved by this method. The semantic-based filtering model can filter web pages selectively with considering a user level and we show in this paper that it is more convenient for users to search information in internet by the proposed method than by traditional filtering methods.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.12
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• pp.1090-1095
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• 2012

In this paper, we propose a model-based fault diagnosis method applied to vibration data. The fault detection is performed by comparing estimated parameters with normal parameters and deciding if the observed changes can be explained satisfactorily in terms of noise or undermodelling. The key feature of this method is that it accounts for the effects of noise and model mismatch. And we aslo design a classifier for the fault isolation by applying the multiclass SVM (Support Vector Machine) to the estimated parameters. The proposed fault detection and isolation methods are applied to an engine vibration data to show a good performance. The proposed fault detection method is compared with a signal-based fault detection method through a performance analysis.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.559-567
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• 2018

In this paper, we propose a new load forecasting method for smart air conditioning (A/C) based on the modified thermodynamics of indoor temperature and the unbiased finite memory estimator (UFME). Based on modified first-order thermodynamics, the dynamic behavior of indoor temperature can be described by the time-domain state-space model, and an accurate estimate of indoor temperature can be achieved by the proposed UFME. In addition, a reliable A/C load forecast can be obtained using the proposed method. Our study involves the experimental validation of the proposed A/C load forecasting method and communication construction between DR server and HEMS in a test bed. Through experimental data sets, the effectiveness of the proposed estimation method is validated.

• Journal of the Korean Society for Railway
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• v.3 no.2
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• pp.43-50
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• 2000

The corrugated panels are the prime candidate structure for the floor, roof and wall of Korean high speed train. The equivalent continuum modeling approach panels can be used for the efficient design and evaluation of their structural characteristics. The equivalent continuum models, derived from the true complex corrugated panels, should have the same structural behavior as the original structures have. This paper briefly reviews three representative continuum modeling methods: the static analysis method and two plate-models based on modal analysis methods (MAM). These methods are evaluated through some numerical examples by comparing the natural frequencies and static deflections. It is observed that the plate-model based on Rayleigh-Ritz method seems to provide the best results when used in conjunction with the cantilever-type boundary conditions. The equivalent elastic constants of various corrugated panels, depending on the changes in their configurations, are tabulated for efficient use in structural design.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.587-590
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• 2004

In this paper proposed a HMM(Hidden Martov Model)-based segmentation method which is able to model shadows as well as foreground and background regions. Shadow of moving objects often obstruct visual tracking. We propose an HMM-based segmentation method which classifies in real time oath objects. In the case of traffic monitoring movies, the effectiveness of the proposed method has been proven through experimental results

• The Journal of the Acoustical Society of Korea
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• v.23 no.6
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• pp.473-480
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• 2004

In this paper we propose an effective feature compensation scheme based on the speech model in order to achieve robust speech recognition. The proposed feature compensation method is based on parallel combined mixture model (PCMM). The previous PCMM works require a highly sophisticated procedure for estimation of the combined mixture model in order to reflect the time-varying noisy conditions at every utterance. The proposed schemes can cope with the time-varying background noise by employing the interpolation method of the multiple mixture models. We apply the‘data-driven’method to PCMM tot move reliable model combination and introduce a frame-synched version for estimation of environments posteriori. In order to reduce the computational complexity due to multiple models, we propose a technique for mixture sharing. The statistically similar Gaussian components are selected and the smoothed versions are generated for sharing. The performance is examined over Aurora 2.0 and speech corpus recorded while car-driving. The experimental results indicate that the proposed schemes are effective in realizing robust speech recognition and reducing the computational complexities under both simulated environments and real-life conditions.

• Journal of Power Electronics
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• v.16 no.6
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• pp.2231-2242
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• 2016

A simplified model predictive control method is presented in this paper. This method is based on a future reference voltage vector for a three-phase four-leg voltage source inverter (VSI). Compared with the three-leg VSIs, the four-leg VSI increases the possible switching states from 8 to 16 owing to a fourth leg. Among the possible states, this should be considered in the model predictive control method for selecting an optimal state. The increased number of candidate switching states and the corresponding voltage vectors increase the calculation burden. The proposed technique can preselect 5 among the 16 possible voltage vectors produced by the three-phase four-leg voltage source inverters, based on the position of the future reference voltage vector. The discrete-time model of the future reference voltage vector is built to predict the future movement of the load currents, and its position is used to choose five preselected vectors at every sampling period. As a result, the proposed method can reduce calculation load by decreasing the candidate voltage vectors used in the cost function for the four-leg VSIs, while exhibiting the same performance as the conventional method. The effectiveness of the proposed method is demonstrated with simulation and experiment results.