• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.12 no.4
• /
• pp.277-284
• /
• 2012

Named entity recognition (NER) technique can play a crucial role in extracting information from the web. While NER systems with relatively high performances have been developed based on careful manipulation of terms with a statistical model, term mismatches often degrade the performance of such systems because the strings of all the candidate entities are not known a priori. Despite the importance of lexical-level term mismatches for NER systems, however, most NER approaches developed to date utilize only the term string itself and simple term-level features, and do not exploit the semantic features of terms which can handle the variations of terms effectively. As a solution to this problem, here we propose to match the semantic concepts of term units in restaurant named entities (NEs), where these units are automatically generated from multiple resolutions of a semantic tree. As a test experiment, we applied our restaurant NER scheme to 49,153 nouns in Korean restaurant web pages. Our scheme achieved an average accuracy of 87.89% when applied to test data, which was considerably better than the 78.70% accuracy obtained using the baseline system.

• Journal of Korean Society for Quality Management
• /
• v.38 no.4
• /
• pp.504-511
• /
• 2010

A fuze detonator comprising star shells is an important device so that its failure usually leads to failure of the shells. In this paper, accelerated degradation tests of RD1333 (lead azide) using temperature stress were performed, and then degradation data of explosive power for the detonator were analyzed to predict the storage lifetime of detonator. Degradation data analysis to estimate the storage lifetime is based on a distribution-based degradation process. Statistical distribution parameters of explosive power degradation measures at each time were estimated for each temperature level, and then reliability of the detonator for each accelerated temperature level was estimated using both time-varying distribution parameters and critical level of explosive power. Arrhenius model was applied to estimate storage lifetime of the detonator under the field temperature condition. Accelerated distribution-based degradation analysis to estimate storage lifetime is explained in detail, and estimation results are compared to field data of storage lifetime in this paper.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2014.10a
• /
• pp.533-538
• /
• 2014

Power generator is one of the most important component of electricity generation system to convert mechanical energy to electrical energy. I t designed robustly to maintain high system reliability during operation time. But unexpected failure of the power generator could happen and it cause huge amount of economic and social loss. To keep it from unexpected failure, health prognostics should be carried out In this research, We developed a health prognostic method of stator windings in power generator with statistical data analysis and degradation modeling against water absorption. We divided whole 42 windings into two groups, absorption suspected group and normal group. We built a degradation model of absorption suspected winding using Fick's second law to predict upcoming absorption data. Through the analysis of data of normal group, we could figure out the distribution of data of normal windings. After that, we can properly predict absorption data of normal windings. With data prediction of two groups, we derived upcoming Directional Mahalanobis Distance (DMD) of absorption suspected winding and time vs DMD curve. Finally we drew the probability distribution of Remaining Useful Life of absorption suspected windings.

• Proceedings of the SAREK Conference
• /
• 2006.06a
• /
• pp.1113-1118
• /
• 2006

A numerical investigation of single phase heat and flow characteristics in circular tubes with a single set of spiral micro fins was performed with varying geometrical parameters like fin height, spiral angle, and number of fins. The properties of $40^{\circ}C$ water was used as a working fluid to simulate a condenser and the RNG $k-{\epsilon}$ turbulence model was adopted. Calculation results were obtained in fully developed turbulent flow with constant surface heat flux boundary condition. Relative terms were introduced to investigate the substitution effect of conventional smooth tubes. The dimensionless terms were the heat transfer enhancement factor, the pressure drop penalty factor, and the efficiency index. Additionally, a numerical optimization was carried out to maximize thermal performance with the concept of the robust design. A statistical analysis showed that fin height interacts with number of fins and spiral angle.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.11 no.9
• /
• pp.3176-3183
• /
• 2010

A multi-scale fatigue life prediction methodology of composite pressure vessels subjected to multi-axial loading has been proposed in this paper. The multi-scale approach starts from the constituents, fiber, matrix and interface, leading to predict behavior of ply, laminates and eventually the composite structures. The multi-scale fatigue life prediction methodology is composed of two steps: macro stress analysis and micro mechanics of failure based on fatigue analysis. In the macro stress analysis, multi-axial fatigue loading acting at laminate is determined from finite element analysis of composite pressure vessel, and ply stresses are computed using a classical laminate theory. The micro stresses are calculated in each constituent from ply stresses using a micromechanical model. Three methods are employed in predicting fatigue life of each constituent, i.e. a maximum stress method for fiber, an equivalent stress method for multi-axially loaded matrix, and a critical plane method for the interface. A modified Goodman diagram is used to take into account the generic mean stresses. Damages from each loading cycle are accumulated using Miner's rule. Monte Carlo simulation has been performed to predict the overall fatigue life of a composite pressure vessel considering statistical distribution of material properties of each constituent, fiber volume fraction and manufacturing winding angle.

• Progress in Superconductivity and Cryogenics
• /
• v.17 no.2
• /
• pp.45-49
• /
• 2015

It has been well known that a toroid is the inevitable shape for a high temperature superconducting (HTS) coil as a component of a large scale superconducting magnetic energy storage system (SMES) because it is the best option to minimize a magnetic field intensity applied perpendicularly to the HTS wires. Even though a perfect toroid coil does not have a perpendicular magnetic field, for a practical toroid coil composed of many HTS pancake coils, some type of perpendicular magnetic field cannot be avoided, which is a major cause of degradation of the HTS wires. In order to suggest an optimum design solution for an HTS SMES system, we need an accurate, fast, and effective calculation for the magnetic field, mechanical stresses, and stored energy. As a calculation method for these criteria, a numerical calculation such as an finite element method (FEM) has usually been adopted. However, a 3-dimensional FEM can involve complicated calculation and can be relatively time consuming, which leads to very inefficient iterations for an optimal design process. In this paper, we suggested an intuitive and effective way to determine the maximum magnetic field intensity in the HTS coil by using an analytic and statistical calculation method. We were able to achieve a remarkable reduction of the calculation time by using this method. The calculation results using this method for sample model coils were compared with those obtained by conventional numerical method to verify the accuracy and availability of this proposed method. After the successful substitution of this calculation method for the proposed design program, a similar method of determining the maximum mechanical stress in the HTS coil will also be studied as a future work.

• Asian-Australasian Journal of Animal Sciences
• /
• v.33 no.10
• /
• pp.1633-1641
• /
• 2020

Objective: The objective of this study was to develop a model for estimating the carcass weight of Hanwoo cattle as a function of body measurements using three different modeling approaches: i) multiple regression analysis, ii) partial least square regression analysis, and iii) a neural network. Methods: Data from a total of 134 Hanwoo cattle were obtained from the National Institute of Animal Science in South Korea. Among the 372 variables in the raw data, 20 variables related to carcass weight and body measurements were extracted to use in multiple regression, partial least square regression, and an artificial neural network to estimate the cold carcass weight of Hanwoo cattle by any of seven body measurements significantly related to carcass weight or by all 19 body measurement variables. For developing and training the model, 100 data points were used, whereas the 34 remaining data points were used to test the model estimation. Results: The R² values from testing the developed models by multiple regression, partial least square regression, and an artificial neural network with seven significant variables were 0.91, 0.91, and 0.92, respectively, whereas all the methods exhibited similar R² values of approximately 0.93 with all 19 body measurement variables. In addition, relative errors were within 4%, suggesting that the developed model was reliable in estimating Hanwoo cattle carcass weight. The neural network exhibited the highest accuracy. Conclusion: The developed model was applicable for estimating Hanwoo cattle carcass weight using body measurements. Because the procedure and required variables could differ according to the type of model, it was necessary to select the best model suitable for the system with which to calculate the model.

• Proceedings of the Korean Geotechical Society Conference
• /
• 1998.05a
• /
• pp.35-81
• /
• 1998

Distinct Element Method(DEM) has a great advantage to model the discontinuous behaviour of jointed rock masses such as rotation, sliding, and separation of rock blocks. Geometrical data of joints by a field monitoring is not enough to model the jointed rock mass though the results of DE analysis for the jointed rock mass is most sensitive to the distributional properties of joints. Also, it is important to use a properly joint law in evaluating the stability of a jointed rock mass because the joint is considered as the contact between blocks in DEM. In this study, a stochastic modelling technique is developed and the dilatant rock joint is numerically modelled in order to consider th geometrical and mechanical properties of joints in DE analysis. The stochastic modelling technique provides a assemblage of rock blocks by reproducing the joint distribution from insufficient joint data. Numerical Modelling of joint dilatancy in a edge-edge contact of DEM enable to consider not only mechanical properties but also various boundary conditions of joint. Preprocess Procedure for a stochastic DE model is composed of a statistical process of raw data of joints, a joint generation, and a block boundary generation. This stochastic DE model is used to analyze the effect of deviations of geometrical joint parameters on .the behaviour of jointed rock masses. This modelling method may be one tool for the consistency of DE analysis because it keeps the objectivity of the numerical model. In the joint constitutive law with a dilatancy, the normal and shear behaviour of a joint are fully coupled due to dilatation. It is easy to quantify the input Parameters used in the joint law from laboratory tests. The boundary effect on the behaviour of a joint is verified from shear tests under CNL and CNS using the numerical model of a single joint. The numerical model developed is applied to jointed rock masses to evaluate the effect of joint dilation on tunnel stability.

• Journal of Advanced Marine Engineering and Technology
• /
• v.33 no.8
• /
• pp.1152-1161
• /
• 2009

The power measurement of main propulsion system on the new vessels can be classified with the direct method acquired from the shaft's strain using strain gauge and the indirect method converted and summed from all of cylinders combustion pressure using mechanical or electrical pickup device during the sea trial. This power is fluctuated by external factors which was influenced by various sea motions with long time interval and by internal factors which was influenced by varying torques of torsional vibration and bending moment, due to mis-aligned shaft and whirling vibration with short time interval. In this paper, the statistical analysis method for the shaft power measurement and assessment using strain gauge in marine vessels are introduced. And these are identified by the low speed two stroke diesel engine model and four stroke medium speed diesel engine model including reduction gear.

• Journal of Biomedical Engineering Research
• /
• v.37 no.1
• /
• pp.21-30
• /
• 2016

Weibull distribution with two parameters, shape (k) and scale (s) parameters are used to model the fatigue failure analysis due to periodic vortex shedding of the synovial fluid in knee joints. In order to determine the later parameter, a suitable statistical model is required for velocity distribution of synovial fluid flow. Hence, wide applicability of Weibull distribution in life testing and reliability analysis can be applied to describe the probability distribution of synovial fluid flow velocity. In this work, comparisons of three most widely used methods for estimating Weibull parameters are carried out; i.e. the least square estimation method (LSEM), maximum likelihood estimator (MLE) and the method of moment (MOM), to study fatigue failure of bone joint due to periodic vortex shedding of synovial fluid. The performances of these methods are compared through the analysis of computer generated synovial fluidflow velocity distribution in the physiological range. Significant values for the (k) and (s) parameters are obtained by comparing these methods. The criterions such as root mean square error (RMSE), coefficient of determination ($R^2$), maximum error between the cumulative distribution functions (CDFs) or Kolmogorov-Smirnov (K-S) and the chi square tests are used for the comparison of the suitability of these methods. The results show that maximum likelihood method performs well for most of the cases studied and hence recommended.