• Journal of Digital Convergence
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• v.12 no.11
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• pp.209-214
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• 2014

Despite the recession of the global market, the domestic electronic appliance companies dominated TV market in North America. They took both the premium and mid-priced product market and achieved both profitability and volume due to strong product competitiveness and brand power. Despite doing well in the North American market, the domestic TV manufacturers are worried about product development, marketing and sales strategies to remain the continuous competitiveness in the TV market. This study proposes the a sales prediction model of electronic appliances using sales data of S company from the North American market. We develop the sales prediction models based on multiple regression analysis and artificial neural network and compare two models. Especially, this study analyzes the relevance between the TV sales and TV main features in order to improve the price competitiveness or improve the value of TV products.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.6
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• pp.1235-1240
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• 2019

It is well known that the ground water level changes rapidly before and after the earthquake, and the variation of ground water level prediction is used to predict the earthquake. In this paper, we predict the ground water level in Miryang City using ANFIS algorithm for earthquake prediction. For this purpose, this paper used precipitation and temperature acquired from National Weather Service and data of underground water level from Rural Groundwater Observation Network of Korea Rural Community Corporation which is installed in Miryang city, Gyeongsangnam-do. We measure the prediction accuracy using RMSE and MAPE calculation methods. As a result of the prediction, the periodic pattern was predicted by natural factors, but the change value of ground water level was changed by other variables such as artificial factors that was not detected. To solve this problem, it is necessary to digitize the ground water level by numerically quantifying artificial variables, and to measure the precipitation and pressure according to the exact location of the observation ball measuring the ground water level.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.07a
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• pp.319-322
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• 2001

The proposed system was composed of pre-processor which was executing binary/high-pass filtering and post-processor which ranged from statistic data to prediction. In post-processor work, step one was filter process of image, step two was image recognition, and step three was destruction degree/time prediction. After these processing, we could predict image of the last destruction timestamp. This research was produced variation value according to growth of tree pattern. This result showed improved correction, when this research was applied image Processing. Pre-processing step of original image had good result binary work after high pass- filter execution. In the case of using partial discharge of the image, our research could predict the last destruction timestamp. By means of experimental data, this Prediction system was acquired ${\pm}$3.2% error range.

• Journal of the Microelectronics and Packaging Society
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• v.22 no.2
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• pp.1-4
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• 2015

Qualification includes all activities to demonstrate that a product meets and exceeds the reliability goals. Manufacturers need to spend time and resources for the qualification processes under the pressure of reducing time to market, as well as offering a competitive price. Failure to qualify a product could result in economic loss such as warranty and recall claims and the manufacturer could lose the reputation in the market. In order to provide valid and reliable qualification results, manufacturers are required to make extra effort based on the operational and environmental characteristics of the product. This paper discusses optimal interval censoring design for reliability prediction of electronic packages under limited time and resources. This design should provide more accurate assessment of package capability and thus deliver better reliability prediction.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.07b
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• pp.607-610
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• 2003

The characteristic prediction and analysis of 3-dimensional (3-D) solenoid-type embedded inductors is investigated. The four different structures of 3-D inductor are fabricated by using low-temperature cofired ceramic (LTCC) process. The circuit model parameters of the each building block are optimized and extracted using the partial element equivalent circuit method and HSPICE circuit simulator. Based on the model parameters, predictive modeling is applied for the structures composed of the combination of the modeled building blocks. And the characteristics of test structures, such as self-resonant frequency, inductance and Q-factor, are analyzed. This approach can provide the characteristic conception of 3-D solenoid embedded inductors for structural variations.

• ETRI Journal
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• v.34 no.4
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• pp.641-644
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• 2012

The problem of sinusoidal parameter estimation at two channels with common frequency in white Gaussian noise is addressed. By making use of the linear prediction property, an iterative linear least squares (LLS) algorithm for accurate frequency estimation is devised. The remaining parameters are then determined according to the LLS fit with the use of the frequency estimate. It is proven that the variance of the frequency estimate achieves Cram$\acute{e}$r-Rao lower bound at sufficiently small noise conditions.

• Journal of the Korean Society for Railway
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• v.9 no.4 s.35
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• pp.419-424
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• 2006

In this paper we study on a method to predict and to demonstrate the reliability of the Korea high speed train control system in quantitative point of view. For the prediction of the reliability in train control system which is composed of electronic parts, Relax Software 7.7 automation tool is employed and MIL-HDBK-217 Handbook that is a standard for the prediction of the failure rate in electronic components is used. Mean Time Between Failure (MTBF) is predicted based on the failure rate of the subsystems, State Modeling and Markov Modeling method is used to express a reliability function of the train control system composed by hardware redundancy as a function of time. We propose a Reliability Test which is performed on the level of the subsystems and Failure Report, Analysing, Correction action system which use the test operation data to prove the predicted reliability.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.210-210
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• 2000

In this paper, we have investigated the properties of multi-layer perceptron (MLP) for odour patterns classification and concentration estimation simultaneously. When the MLP may be has a fast convergence speed with small error and excellent mapping ability for classification, it can be possible to use for classification and concentration prediction of volatile chemicals simultaneously. However, the conventional MLP, which is back-Propagation of error based on the steepest descent method, was difficult to use for odour classification and concentration estimation simultaneously, because it is slow to converge and may fall into the local minimum. We adapted the Levenberg-Marquardt(LM) algorithm [4,5] having advantages both the steepest descent method and Gauss-Newton method instead of the conventional steepest descent method for the simultaneous classification and concentration estimation of odours. And, We designed the artificial odour sensing system(Electronic Nose) and applied LM-BP algorithm for classification and concentration prediction of VOC gases.

• Structural Engineering and Mechanics
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• v.45 no.2
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• pp.201-209
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• 2013

A new dynamic reliability analysis of structure under repeated random loads is proposed in this paper. The proposed method is developed based on the idea that the probability density of several times random loads can be derived from the probability density of single-time random load. The reliability prediction models of structure based on time responses under several times random loads with and without strength degradation are obtained by using the stress-strength interference theory and probability density evolution method. The resulting differential equations in the prediction models can be solved by using the forward finite difference method. Then, the probability density functions of strength redundancy of the structures can be obtained. Finally, the structural dynamic reliability can be calculated using integral method. The efficiency of the proposed method is demonstrated numerically through a speed reducer. The results have shown that the proposed method is practicable, feasible and gives reasonably accurate prediction.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.17 no.4
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• pp.25-31
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• 2009

In development phase of the Aircraft Systems, the reliability prediction of electronic equipments are usually performed using MIL-HDBK-217. The reliability of fielded electronic systems, however, used to be underestimated with MIL-HDBK-217. To solve this problem, some alternatives are suggested and Telcordia SR-332 is among them. In this case study, the reliability of ESU which controls gas turbine engine is predicted using Telcordia SR-332 along with the development test data. The predicted reliabilities of ESU using Telcordia SR-332 and MIL-HDBK-217 are also compared. As a result this case study showed that the predicted reliability using Telcordia SR-332 was better close to field(operation) reliability than MIL-HDBK-217.