• Journal of Industrial Technology
• /
• v.29 no.A
• /
• pp.27-36
• /
• 2009

Reliability plays a pivotal role in products safety and quality. DoD RIAC recently developed a new reliability prediction methodology, $217Plus^{TM}$, for electronic systems. It officially replaces the well-known MIL-HDBK-217 and is expected to be widely used. Although theoretic study about $217Plus^{TM}$ and its application towards field systems seem to be attractive, it is also desirable to understand the general background of its development. In this paper, we performed a historical review of the arenas related to reliability prediction. Due to the vast of materials, our scope was limited to the development of $217Plus^{TM}$. We first reviewed Rome Laboratory and RIAC. We then explained the development course of reliability methods, MIL-HDBK-217, PRISM, and 217-Plus. This review will form not only a good understanding of the methodology but a basis for future study. We conclude this study with provision of future research areas.

• Journal of The Korean Association For Science Education
• /
• v.24 no.5
• /
• pp.814-824
• /
• 2004

This article presents the effects of estimation activities related to speed and density on students' concept-understanding, answer-prediction, and answer-calculation in problem solving procedure with quantitative and qualitative methods. Participants were one hundred and ninety two seventh graders from one coeducational school in Seoul. Half of them participated in the estimation activities and the other half did in the measurement activities. Discussions of three students during estimation activities on density and their post-interviews were tape-recorded. Pre- and post-assessment scores were analyzed for the whole classes, and students' discussions and interviews served this research as evidences for the case analysis. Results of scores indicated that students in the estimation activities were significantly better than those in the measurement activities for predicting answers, but not for understanding concepts. Analysis of the cases revealed that estimation activity helped them to understand the relations of mass, volume and density, empirically, which enhanced their prediction ability. Furthermore, the ability could help a student with low calculation ability to comprehend the calculation problems. Thus, it is concluded that estimation activities could influence students' empirical learning on quantitative concepts, which enhanced their prediction ability.

• Advances in nano research
• /
• v.3 no.3
• /
• pp.143-168
• /
• 2015

Initiation of crack and its growth simulation requires accurate model of traction - separation law. Accurate modeling of traction-separation law remains always a great challenge. Atomistic simulations based prediction has great potential in arriving at accurate traction-separation law. The present paper is aimed at establishing a method to address the above problem. A method for traction-separation law prediction via utilizing atomistic simulations data has been proposed. In this direction, firstly, a simpler approach of common neighbor analysis (CNA) for the prediction of crack growth has been proposed and results have been compared with previously used approach of threshold potential energy. Next, a scheme for prediction of crack speed has been demonstrated based on the stable crack growth criteria. Also, an algorithm has been proposed that utilizes a variable relaxation time period for the computation of crack growth, accurate stress behavior, and traction-separation atomistic law. An understanding has been established for the generation of smoother traction-separation law (including the effect of free surface) from a huge amount of raw atomistic data. A new curve fit has also been proposed for predicting traction-separation data generated from the molecular dynamics simulations. The proposed traction-separation law has also been compared with the polynomial and exponential model used earlier for the prediction of traction-separation law for the bulk materials.

• Journal of Korea Water Resources Association
• /
• v.39 no.9 s.170
• /
• pp.755-766
• /
• 2006

Since the accuracy of climate forecast information has improved from better understanding of the climatic system, particularly, from the better understanding of ENSO and the improvement in meteorological models, the forecasted climate information is becoming the important clue for streamflow prediction. This study investigated the available climate forecast information to improve the extended streamflow prediction in Korea, such as MIMI(Monthly Industrial Meteorological Information) and GDAPS(Global Data Assimilation and Prediction) and measured their accuracies. Both MIMI and the 10-day forecast of GDAPS were superior to a naive forecasts and peformed better for the flood season than for the dry season, thus it was proved that such climate forecasts would be valuable for the flood season. This study then forecasted the monthly inflows to Chungju Dam by using MIMI and GDAPS. For MIMI, we compared three cases: All, Intersection, Union. The accuracies of all three cases are better than the naive forecast and especially, Extended Streamflow Predictions(ESPs) with the Intersection and with Union scenarios were superior to that with the All scenarios for the flood season. For GDAPS, the 10-day ahead streamflow prediction also has the better accuracy for the flood season than for the dry season. Therefore, this study proved that using the climate information such as MIMI and GDAPS to reduce the meteorologic uncertainty can improve the accuracy of the extended streamflow prediction for the flood season.

• Interdisciplinary Bio Central
• /
• v.4 no.4
• /
• pp.14.1-14.6
• /
• 2012

Splice site prediction in DNA sequence is a basic search problem for finding exon/intron and intron/exon boundaries. Removing introns and then joining the exons together forms the mRNA sequence. These sequences are the input of the translation process. It is a necessary step in the central dogma of molecular biology. The main task of splice site prediction is to find out the exact GT and AG ended sequences. Then it identifies the true and false GT and AG ended sequences among those candidate sequences. In this paper, we survey research works on splice site prediction based on support vector machine (SVM). The basic difference between these research works is nucleotide encoding technique and SVM kernel selection. Some methods encode the DNA sequence in a sparse way whereas others encode in a probabilistic manner. The encoded sequences serve as input of SVM. The task of SVM is to classify them using its learning model. The accuracy of classification largely depends on the proper kernel selection for sequence data as well as a selection of kernel parameter. We observe each encoding technique and classify them according to their similarity. Then we discuss about kernel and their parameter selection. Our survey paper provides a basic understanding of encoding approaches and proper kernel selection of SVM for splice site prediction.

• Asia pacific journal of information systems
• /
• v.30 no.1
• /
• pp.31-52
• /
• 2020

Stock markets are popular investment avenues to people who plan to receive premium returns compared to other financial instruments, but they are highly volatile and risky due to the complex financial dynamics and poor understanding of the market forces involved in the price determination. A system that can forecast, predict the stock prices and automatically create a portfolio of top performing stocks is of great value to individual investors who do not have sufficient knowledge to understand the complex dynamics involved in evaluating and predicting stock prices. In this paper the authors propose a Stock prediction, Portfolio Generation and Selection model based on Machine learning algorithms, Artificial neural networks (ANNs) are used for stock price prediction, Mathematical and Statistical techniques are used for Portfolio generation and Un-Supervised Machine learning based on K-Means Clustering algorithms are used for Portfolio Evaluation and Selection which take in to account the Portfolio Return and Risk in to consideration. The model presented here is limited to predicting stock prices on a long term basis as the inputs to the model are based on fundamental attributes and intrinsic value of the stock. The results of this study are quite encouraging as the stock prediction models are able predict stock prices at least a financial quarter in advance with an accuracy of around 90 percent and the portfolio selection classifiers are giving returns in excess of average market returns.

• Wind and Structures
• /
• v.2 no.4
• /
• pp.325-345
• /
• 1999

In recent years, rainscreen walls based on the pressure equalization principle are often used in building construction. To improve the understanding of the influence of several design parameters on the pressure equalization performance of such wall systems, a theoretical consideration of the problem may be more appropriate. On this basis, this paper presents two theoretical models, one based on mass balance and the other based on the Helmholtz resonator theory, for the prediction of cavity pressure in rigid rainscreen walls. New measures to assess the degree of pressure equalization of rainscreen walls are also suggested. The results show that the model based on mass balance is sufficiently accurate and efficient in predicting the cavity pressure variations. Further, the performance of the proposed model is evaluated utilizing the data obtained from full-scale tests and the results are discussed in detail.

• BMB Reports
• /
• v.42 no.11
• /
• pp.697-704
• /
• 2009

Membrane proteins play important roles in the biology of the cell, including intercellular communication and molecular transport. Their well-established importance notwithstanding, the high-resolution structures of membrane proteins remain elusive due to difficulties in protein expression, purification and crystallization. Thus, accurate prediction of membrane protein topology can increase the understanding of membrane protein function. Here, we provide a brief review of the diverse computational methods for predicting membrane protein structure and function, including recent progress and essential bioinformatics tools. Our hope is that this review will be instructive to users studying membrane protein biology in their choice of appropriate bioinformatics methods.

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2004.08a
• /
• pp.349-358
• /
• 2004

The strip temperature history of finishing mill process is one of the most important factors to stabilize the facilities and to achieve the better product quality including a better prediction of roll force etc. The ultimate goal of this study is to improve scientific understanding of the finishing mill process in the view of heat transfer science. Finishing mill cooling facilities of KwangYang $\#3$ hot rolling are introduced and heat transfer analyses from FET to FDT are particularly focused in this study Three major tasks are successfully achieved as follows: 1) The temperature Prediction Models are developed. 2) The average absolute error is found to be less then 10 Celsius degree (about $8.5^{\circ}C$). 3) Prediction rate (less then $\bar{+}20$) are $10.2\%$ improved $(80.1\;\rightarrow\;90.3\%)$.

• Journal of Environmental Impact Assessment
• /
• v.22 no.1
• /
• pp.109-116
• /
• 2013

By IPCC climate change scenario, the socioeconomic actions such as the land use change are closely associated with the climate change as an up zoning action of urban development to increase green gas emission to atmosphere. Prediction of the land use change with rational quality can provide better data for understanding of the climate change in future. This study aims to predict land use change of Cheongju in future and SLEUTH model is used to anticipate with the status quo condition, in which the pattern of land use change in future follows the chronical tendency of land use change during last 25 years. From 40 years prediction since 2000 year, the area urbanized compared with 2000 year increases up to 87.8% in 2040 year. The ratios of the area urbanized from agricultural area and natural area in 2040 are decreased to 53.1% and 15.3%, respectively.