• Journal of Information Processing Systems
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• v.17 no.3
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• pp.462-472
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• 2021

With an increase in the scale of recommender systems, users' rating data tend to be extremely sparse. Some methods have been utilized to alleviate this problem; nevertheless, it has not been satisfactorily solved yet. Therefore, we propose an effective pre-rating method based on users' dichotomous preferences and average ratings fusion. First, based on a user-item ratings matrix, a new user-item preference matrix was constructed to analyze and model user preferences. The items were then divided into two categories based on a parameterized dynamic threshold. The missing ratings for items that the user was not interested in were directly filled with the lowest user rating; otherwise, fusion ratings were utilized to fill the missing ratings. Further, an optimized parameter λ was introduced to adjust their weights. Finally, we verified our method on a standard dataset. The experimental results show that our method can effectively reduce the prediction error and improve the recommendation quality. As for its application, our method is effective, but not complicated.

• Magazine of the Korean Society of Agricultural Engineers
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• v.40 no.5
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• pp.91-99
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• 1998

The widespread use of thin shell structures has created a need for a systematic method of analysis which can adequately account for arbitrary geometric form and boundary conditions as well as arbitrary general type of loading. Therefore, the stress and analysis of thin shell has been one of the more challenging areas of structural mechanics. A wide variety of numerical methods have been applied to the governing differential equations for spherical and cylindrical structures with a few results applicable to practice. The analysis of axisymmetric spherical shell is almost an every day occurrence in many industrial applications. A reliable and accurate finite element analysis procedure for such structures was needed. Dynamic loading of structures often causes excursions of stresses well into the inelastic range and the influence of geometry changes on the response is also significant in many cases. Therefore both material and geometric nonlinear effects should be considered. In general, the shell structures designed according to quasi-static analysis may fail under conditions of dynamic loading. For a more realistic prediction on the load carrying capacity of these shell, in addition to the dynamic effect, consideration should also include other factors such as nonlinearities in both material and geometry since these factors, in different manner, may also affect the magnitude of this capacity. The objective of this paper is to demonstrate the dynamic characteristics of spherical shell. For these purposes, the spherical shell subjected to uniformly distributed step load was analyzed for its large displacements elasto-viscoplastic static and dynamic response. Geometrically nonlinear behaviour is taken into account using a Total Lagrangian formulation and the material behaviour is assumed to elasto-viscoplastic model highly corresponding to the real behaviour of the material. The results for the dynamic characteristics of spherical shell in the cases under various conditions of base-radius/central height(a/H) and thickness/shell radius(t/R) were summarized as follows : The dynamic characteristics with a/H. 1) AS the a/H increases, the amplitude of displacement in creased. 2) The values of displacement dynamic magnification factor (DMF) were ranges from 2.9 to 6.3 in the crown of shell and the values of factor in the mid-point of shell were ranged from 1.8 to 2.6. 3) As the a/H increases, the values of DMF in the crown of shell is decreased rapidly but the values of DMF in mid-point shell is increased gradually. 4) The values of DMF of hoop-stresses were range from 3.6 to 6.8 in the crown of shell and the values of factor in the mid-point of shell were ranged from 2.3 to 2.6, and the values of DMF of stress were larger than that of displacement. The dynamic characteristics with t/R. 5) With the thickness of shell decreases, the amplitude of the displacement and the period increased. 6) The values of DMF of the displacement were ranged from 2.8 to 3.6 in the crown of shell and the values of factor in the mid-point of shell were ranged from 2.1 to 2.2.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2009.10a
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• pp.223-226
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• 2009

The plastics are widely utilized in the inside of vehicles. The dynamic tensile characteristics of auto-body plastics are important in a prediction of deformation mode of the plastic component which undergoes the high speed deformation during car crash. This paper is concerned with the dynamic tensile characteristics of the auto-body plastics at intermediate strain rates. Quasi-static tensile tests were carried out at the strain rate ranged from 0.001/sec to 0.01/sec using the static tensile machine(Instron 5583). Dynamic tensile tests were carried out at the strain rate ranged from 0.1/sec to 100/sec using the high speed material testing machine developed. Conventional extensometry method is no longer available for plastics, since the deformation of plastic is accompanied with localized deformation. In this paper, quasi-static and dynamic tensile tests were performed using ASTM IV standard specimens with grids and images from a high speed camera were analyzed for strain measurement. True stress-strain relations and the actual strain rates at each deformation step were obtained by processing load data and deformation images, assuming the plastics to deform uniformly in each grid.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.38 no.1
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• pp.1-13
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• 2001

In this paper, we propose a new dynamic bandwidth allocation and call admission control for VBR video sources with QoS constraints to support an efficient resource management and at the same Lime to satisfy the user's quality or service requirements. For the dynamic bandwidth allocation, first the next amount of traffic is predicted using a modified adaptive linear prediction method that considers abrupt scene change effects. And then, we dynamically allocate the necessary bandwidth to each connection based on the currently provided quality degree by the network with respect to the user's QoS requirements in terms of average delay and loss ratio. For the admission control, we determine the acceptance or rejection or a new connection based on the quality satisfaction degrees of the existing connections. Simulation results show that our proposed dynamic schemes are able to provide a stable service, which well meets the user's quality requirements.

• Journal of the Korea institute for structural maintenance and inspection
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• v.15 no.6
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• pp.110-117
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• 2011

Seashore landfill projects use undersea pump dredging method for construction of airport and factory site. Coarse grain soil from the dredging is considered for use at inland. West sea shore bottom consists of primarily coarser grained silt-sand and this component contains far more percentage than is the case with East sea and South sea area. This soil shows very different characteristic at consolidation and compaction behavior. This research targets to utilize this type of dredging soil. Test specimen is from West sea (Saemangum) dredged soil landfill site. Model analysis is done for getting prediction of original soil relative density and N-value from dynamic compaction energy variance. Dynamic compaction energy is calculated for efficient foundation design.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.6
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• pp.158-169
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• 2004

A method for predicting the short-term dynamic line ratings in overhead transmission lines using real-time weather forecast data is proposed in this paper. Through some inspections for the 3-hour interval forecasting factors such as ambient temperature, wind speed grade and weather code given by KMA(Korea Meteorological Administration), correlation properties between forecast weather data and actual measured data are analyzed. To use these variable in determining the dynamic line ratings, they are changed into suitable numerical values. Furthermore adaptive neuro-fuzzy systems to improve reliabilities for wind speed and solar heat radiation ate designed It was verified that the forecast weather data can be used to predict the line rating with reliable. As a result it can be possible that the proposed predicting system can be effectively utilized by their anticipation a short-time in advance.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.139-157
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• 2016

Bankruptcy involves considerable costs, so it can have significant effects on a country's economy. Thus, bankruptcy prediction is an important issue. Over the past several decades, many researchers have addressed topics associated with bankruptcy prediction. Early research on bankruptcy prediction employed conventional statistical methods such as univariate analysis, discriminant analysis, multiple regression, and logistic regression. Later on, many studies began utilizing artificial intelligence techniques such as inductive learning, neural networks, and case-based reasoning. Currently, ensemble models are being utilized to enhance the accuracy of bankruptcy prediction. Ensemble classification involves combining multiple classifiers to obtain more accurate predictions than those obtained using individual models. Ensemble learning techniques are known to be very useful for improving the generalization ability of the classifier. Base classifiers in the ensemble must be as accurate and diverse as possible in order to enhance the generalization ability of an ensemble model. Commonly used methods for constructing ensemble classifiers include bagging, boosting, and random subspace. The random subspace method selects a random feature subset for each classifier from the original feature space to diversify the base classifiers of an ensemble. Each ensemble member is trained by a randomly chosen feature subspace from the original feature set, and predictions from each ensemble member are combined by an aggregation method. The k-nearest neighbors (KNN) classifier is robust with respect to variations in the dataset but is very sensitive to changes in the feature space. For this reason, KNN is a good classifier for the random subspace method. The KNN random subspace ensemble model has been shown to be very effective for improving an individual KNN model. The k parameter of KNN base classifiers and selected feature subsets for base classifiers play an important role in determining the performance of the KNN ensemble model. However, few studies have focused on optimizing the k parameter and feature subsets of base classifiers in the ensemble. This study proposed a new ensemble method that improves upon the performance KNN ensemble model by optimizing both k parameters and feature subsets of base classifiers. A genetic algorithm was used to optimize the KNN ensemble model and improve the prediction accuracy of the ensemble model. The proposed model was applied to a bankruptcy prediction problem by using a real dataset from Korean companies. The research data included 1800 externally non-audited firms that filed for bankruptcy (900 cases) or non-bankruptcy (900 cases). Initially, the dataset consisted of 134 financial ratios. Prior to the experiments, 75 financial ratios were selected based on an independent sample t-test of each financial ratio as an input variable and bankruptcy or non-bankruptcy as an output variable. Of these, 24 financial ratios were selected by using a logistic regression backward feature selection method. The complete dataset was separated into two parts: training and validation. The training dataset was further divided into two portions: one for the training model and the other to avoid overfitting. The prediction accuracy against this dataset was used to determine the fitness value in order to avoid overfitting. The validation dataset was used to evaluate the effectiveness of the final model. A 10-fold cross-validation was implemented to compare the performances of the proposed model and other models. To evaluate the effectiveness of the proposed model, the classification accuracy of the proposed model was compared with that of other models. The Q-statistic values and average classification accuracies of base classifiers were investigated. The experimental results showed that the proposed model outperformed other models, such as the single model and random subspace ensemble model.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.89-90
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• 2008

This paper studies the effect of pad at initial stage and wear during braking on the dynamic contact pressure distribution. Wear is influenced by variable factor (contact pressure, sliding speed, radius, temperature) during dynamic braking and variation in contact pressure distribution. Many researchers have conducted complex eigenvalue analysis considering wear characteristic with Lim and Ashby wear map. The conventional analysis method is assumed the pad has smooth and flat surfaces. The purpose of this paper is to validate that wear rate induced by braking is considered for the precise squeal prediction. After obtaining pad wear from experiment, it is incorporated with FE model of brake system. Finally, the comparisons in fugitive nature of squeal will be carried out between the complex eigenvalue analysis and noise dynamometer experiment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1808-1811
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• 2005

The prediction of AOV(air-operated valve) performance is normally evaluated by the allowable opening thrust margin for the opening and closing stroke. However, it is not easy to carry out the dynamic test measurement for all the valves in the nuclear power plant due to the safety and operating conditions. The analysis of the available and required thrust for the valve is simulated as an alternate method to turn around this obstacle. The required air pressures to the stem displacement are discussed for differential valve pressure obtained by experiment. The result of the simulation is compared with that of the experiment. SIMULINK in MATLAB was used for the simulation and the results show good agreement with the actual test carried out with Fisher globe valve.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.12
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• pp.3149-3158
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• 1994

In this paper, using the formulation of dynamic equivalent load considering the effects of moment load and the equation to estimate the cage rotational speed, the new life equation of deep groove ball bearing under radial and moment loads was proposed. Fatigue life test apparatus with the measuring equipment of shaft and cage speed was designed and developed to be capable of subjecting combined radial and moment load. Fatigue life tests were executed by sudden death test method and the reliability of fatigue lives was evaluated by Weibull distribution analysis. From the results of fatigue tests and analysis, the relationships between film parameters and life adjustment factors were acquired. And it was turned out that so as to estimate the effect of moment load on fatigue life, the life adjustment factor as well as the dynamic equivalent load must be taken into account.