• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.1
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• pp.124-131
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• 2012

This paper presents a spreadsheet-based reliability prediction simulation framework for the conceptual product design stage to acquire system reliability information in timely manner. During early stage, reliability performance deals with both known and unknown failure rates and component-level and subsystem-level failure estimate to predict system reliability. A technique for performing life testing simulation using Excel spreadsheet has been developed under the such circumstances. This paper also discuss the results obtainable from this method such as reliability estimate, mean and variance of failures and confidence intervals. The resultant of this reliability prediction system is mainly benefitting small and medium-sized enterprise's field engineers.

• Proceedings of the Korea Concrete Institute Conference
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• 1997.10a
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• pp.143-150
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• 1997

The maturity concept was adopted to predict the strength of concrete, which was subjected to same temperature conditions and variable curing conditions. Penetration test and compressive test were conducted to measure the initial and final setting time and the compressible strength of concrete specimen, respectively. Also, the temperature and time were recorded at some intervals of time for calculating the maturity. The initial and final setting were delayed as the w/c ratio increased and curing temperature decreased. The activating energy decreased as the w/c ratio increased. The relationships at the relative strength and the maturity were proposed at different w/c ratio for the same temperature curing condition, and these were applied for the variable curing conditions. The results indicated that the difference between the strength of the proposed and the specimen was big at 1 days's age but quite similar after 3 day's age.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.428-428
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• 2000

A robust intelligent algorithm for AGV navigation control is presented here based on both magnetic and gyro sensors to track a reference trajectory. Since the proposed system uses an intermittent array of short magnetic tape strips, it lends itself to a very easy installation and maintenance compared to other types of positioning references such as electric wire, magnets, RF and laser beacons. The neural network is to predict the lateral deviation of the AGV in the intervals where no magnetic tape references are available. Further, the use of intelligent control ensures a robust and flexible control performance. Computer simulation of AGV control demonstrates its adequate tracking performances even where the sensor information is not available. Real experiments using Samsung AGV are also on the way for real verification

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.3
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• pp.294-300
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• 2009

In high speed railway bridges, dynamic analysis is important because of high passing velocity and moving load at the regular intervals, and damping ratio is a major parameter to predict dynamic responses. In this paper, damping ratios were estimated by using half power band width method and extended Kalman filter according to acceleration signal conditions, and a relationship between estimated damping ratios and representative values of bridge vibration was derived. From the results, damping ratios estimated from total ambient vibration were more reliable than only free vibration part. In case of using extended Kalman filter, the estimated damping ratios varying with RMQ(root mean quad), as one of representative values of bridge vibration, have more feasible trend. Thus, it is shown that further studies on reliabilities of estimated damping ratios are needed.

• Transactions on Electrical and Electronic Materials
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• v.6 no.6
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• pp.256-261
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• 2005

This paper presents that the modeling to predict the characteristics with respect to the performance of solenoid embedded inductors manufactured by LTCC process via the nonlinear regression model based on the quasi-Newton method. In order to reduce the runs, the design of experiments (DOE) was used to generate the design space. The nonlinear process models were constructed by the piecewise regression model based on the quasi-Newton method for estimating the model coefficient with the break point on the statistical confidence intervals. Those models were verified by the model accuracy checking based on the assumption statistically.

• Journal of the Korean Society of Safety
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• v.8 no.2
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• pp.51-57
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• 1993

This study was done by ultrasonic testing. The proves used in this study were 5Z10$\times$10A70. The useful fatigue life of structural components is determined by the sum of the elapsed load cycles required to initiate a fatigue crack and to propagate the crack from subcritical size to critical dimensions. Thus, to predict the service life of many steel structures and to establish safe inspection intervals, an understanding of the Fatigue Crack Initiation and Fatigue Crack Propagation behavior in the steel is required. In the present study, the Fatigue Crack Initiation Life in SPS 5A steel was investigated by testing specimens having widely varying notch acuities. The variation in the notch acuity covered the range from notch root raidus 0.5mm to 2.5mm, and Fatigue Crack Initiation Life data were obtained in that range.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.12
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• pp.65-72
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• 2018

The purpose of this study is to predict vertical illuminance accurately at the design stage of a building without the help of simulation tools. Comparing two well-known vertical illuminance prediction algorithms with measured values, it is verified that the Igawa model is more consistent with the measured values than the Perez model. Using the DIVA program, we simulated the vertical illuminance at 30-degree intervals from south to north, compared with the vertical illuminance calculated with the Igawa model. The result of calculation values were verified from 120 degrees east to 120 degrees west. The vertical illuminance values with each of three shade devices were calculated using the Igawa model, and compared with the vertical illuminance simulated by DIVA program. As a result, all the errors when installing horizontal / vertical / grid shade divices were included in the error standard specified by ASHRAE.

• Molecules and Cells
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• v.44 no.12
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• pp.883-892
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• 2021

Genome-wide chromosome conformation capture (3C)-based high-throughput sequencing (Hi-C) has enabled identification of genome-wide chromatin loops. Because the Hi-C map with restriction fragment resolution is intrinsically associated with sparsity and stochastic noise, Hi-C data are usually binned at particular intervals; however, the binning method has limited reliability, especially at high resolution. Here, we describe a new method called HiCORE, which provides simple pipelines and algorithms to overcome the limitations of single-layered binning and predict core chromatin regions with three-dimensional physical interactions. In this approach, multiple layers of binning with slightly shifted genome coverage are generated, and interacting bins at each layer are integrated to infer narrower regions of chromatin interactions. HiCORE predicts chromatin looping regions with higher resolution, both in human and Arabidopsis genomes, and contributes to the identification of the precise positions of potential genomic elements in an unbiased manner.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.797-804
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• 2006

A development of regression model for asphalt concrete pavements using Falling Weight Deflectometer deflections is presented in this paper. A backcalculation program based on layered elastic theory was used to generate the synthetic modulus database, which was used to generate 95% confidence intervals of modulus in each layer. Using deflection basins of FWD data used in developing this procedure were collected from Pavement Management System in flexible pavements. Assumptions of back-calculation are that one is 3 layered flexible pavement structure and another is depth to bedrock is finite. It is found that difference of between 95% confidence intervals and modulus ranges of other papers does not exist. So, the data of 95% confidence intervals in each layer was used to develop multiple regression models. Multiple regression equations of each layer were established by SPSS, package of Statics analysis. These models were proved by regression diagnostics, which include case analysis, multi-collinearity analysis, influence diagnostics and analysis of variance. And these models have higher degree of coefficient of determination than 0.75. So this models were applied to predict modulus of domestic asphalt concrete pavement at FWD field test.

• Journal of Information Technology Services
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• v.19 no.4
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• pp.49-61
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• 2020

Prior studies on technology predictions attempted to predict the emergence and spread of emerging technologies through the analysis of correlations and changes between data using objective data such as patents and research papers. Most of the previous studies predicted future technologies only from the viewpoint of technology development. Therefore, this study intends to conduct technical forecasting from the perspective of the consumer by using keyword search frequency of search portals such as NAVER before and after the introduction of emerging technologies. In this study, we analyzed healthcare technologies into three types : measurement technology, platform technology, and remote service technology. And for the keyword analysis on the healthcare, we converted the classification of technology perspective into the keyword classification of consumer perspective. (Blood pressure and blood sugar, healthcare diagnosis, appointment and prescription, and remote diagnosis and prescription) Naver Trend is used to analyze keyword trends from a consumer perspective. We also used the ARIMA model as a technology prediction model. Analyzing the search frequency (Naver trend) over 44 months, the final ARIMA models that can predict three types of healthcare technology keyword trends were estimated as "ARIMA (1,2,1) (1,0,0)", "ARIMA (0,1,0) (1,0,0)", "ARIMA (1,1,0) (0,0,0)". In addition, it was confirmed that the values predicted by the time series prediction model and the actual values for 44 months were moving in almost similar patterns in all intervals. Therefore, we can confirm that this time series prediction model for healthcare technology is very suitable.