• ETRI Journal
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• v.36 no.3
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• pp.418-428
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• 2014

In social network services, such as Facebook, Google+, Twitter, and certain postings attract more people than others. In this paper, we propose a novel method for predicting the lifespan and retweet times of tweets, the latter being a proxy for measuring the popularity of a tweet. We extract information from retweet graphs, such as posting times; and social, local, and content features, so as to construct prediction knowledge bases. Tweets with a similar topic, retweet pattern, and properties are sequentially extracted from the knowledge base and then used to make a prediction. To evaluate the performance of our model, we collected tweets on Twitter from June 2012 to October 2012. We compared our model with conventional models according to the prediction goal. For the lifespan prediction of a tweet, our model can reduce the time tolerance of a tweet lifespan by about four hours, compared with conventional models. In terms of prediction of the retweet times, our model achieved a significantly outstanding precision of about 50%, which is much higher than two of the conventional models showing a precision of around 30% and 20%, respectively.

• Corrosion Science and Technology
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• v.18 no.3
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• pp.86-91
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• 2019

Generally, atmospheric corrosion is the electrochemical degradation of metal that can be caused by various corrosion factors of atmospheric components and weather, as well as air pollutants. Specifically, moisture and particles of sea salt and sulfur dioxide are major factors in atmospheric corrosion. Using galvanized steel is one of the most efficient ways to protect iron from corrosion by zinc plating on the surface of the iron. Galvanized steel is widely used in automobiles, building structures, roofing, and other industrial structures due to their high corrosion resistance relative to iron. The atmospheric corrosion of galvanized steel shows complex corrosion behavior, depending on the plating, coating thickness, atmospheric environment, and air pollutants. In addition, corrosion products are produced in different types of environments. The lifespans of galvanized steels may vary depending on the use environment. Therefore, this study investigated the corrosion behavior of galvannealed steel under atmospheric corrosion in two locations in Korea, and the lifespan prediction of galvannealed steel in rural and coastal environments was conducted by means of the potentiostatic dissolution test and the chemical cyclic corrosion test.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.424-429
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• 2018

In this study, an expansion joint that is susceptible to waterhammer was tested for its vibration durability. The operation data for the hydraulic actuator was the expansion length of the expansion joint when the waterhammer occurred. In the case of the vibration durability test, the internal temperature status of the expansion joint was assumed to be a stress factor and a lifespan prediction model was assumed to follow the Arrhenius model. A test was carried out by increasing the internal temperature status at $30^{\circ}C$, $50^{\circ}C$, and $65^{\circ}C$. By a linear transformation of the lifespan data for each temperature, a constant value and activation energy coefficient was induced for the Arrhenius equation and verified by comparing the value of a lifetime prediction model with the experimental value at $85^{\circ}C$. The failure modes of the ongoing or finished test were leakage, bellows separation, and internal deformation. In the future, a composite lifespan prediction model, including two more stress factors, will be developed.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.5
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• pp.58-63
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• 2018

Recently in weapon systems development, the importance of reliability has been emphasized due to the increase in complexity and the rapid development of key components and components. Accordingly, the importance of lifespan testing is increased. However, lifespan testing to verify the reliability of a system is costly and takes a lot of time. Therefore in this paper, it was demonstrated that the most critical item of a bladder type accumulator is the bladder. Fatigue life is sensitive to temperature and pressure, with temperature having more impact. The fatigue life of the bladder was estimated to be 18,140 hr through fatigue analysis, which satisfies the required life expectancy of 10,000 hr.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.113-132
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• 2021

This study is a new evaluation using the Arrhenius equation, which is known as the chemical reaction rate estimation equation, to evaluate the intrinsic and extrinsic value elements of patents as a model. The performance of the evaluation model was superior to the SVM, Logistic reg. and ANN models that were used as patent evaluation models in prior studies. In addition, there was a strong correlation between the predicted lifespan of the patent and the actual lifespan of the patent. These evaluation models may be used for evaluation purposes only, or if an evaluation is required, including a commercialization entity or technical characteristics.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.147-170
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• 2022

Although the number of patent which is one of the core outputs of technological innovation continues to increase, the number of low-value patents also hugely increased. Therefore, efficient evaluation of patents has become important. Estimation of patent lifespan which represents private value of a patent, has been studied for a long time, but in most cases it relied on a linear model. Even if machine learning methods were used, interpretation or explanation of the relationship between explanatory variables and patent lifespan was insufficient. In this study, patent lifespan (number of renewals) is predicted based on the idea that patent lifespan represents the value of the patent. For the research, 4,033,414 patents applied between 1996 and 2017 and finally granted were collected from USPTO (US Patent and Trademark Office). To predict the patent lifespan, we use variables that can reflect the characteristics of the patent, the patent owner's characteristics, and the inventor's characteristics. We build four different models (Ridge Regression, Random Forest, Feed Forward Neural Network, Gradient Boosting Models) and perform hyperparameter tuning through 5-fold Cross Validation. Then, the performance of the generated models are evaluated, and the relative importance of predictors is also presented. In addition, based on the Gradient Boosting Model which have excellent performance, Accumulated Local Effects Plot is presented to visualize the relationship between predictors and patent lifespan. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the evaluation reason of individual patents, and discuss applicability to the patent evaluation system. This study has academic significance in that it cumulatively contributes to the existing patent life estimation research and supplements the limitations of existing patent life estimation studies based on linearity. It is academically meaningful that this study contributes cumulatively to the existing studies which estimate patent lifespan, and that it supplements the limitations of linear models. Also, it is practically meaningful to suggest a method for deriving the evaluation basis for individual patent value and examine the applicability to patent evaluation systems.

• Journal of Information Processing Systems
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• v.18 no.4
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• pp.457-469
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• 2022

Hydraulic concrete buildings in the northwest of China are often subject to the combined effects of low-temperature frost damage, during drying and wetting cycles, and salt erosion, so the study of concrete deterioration prediction is of major importance. The prediction model of the relative dynamic elastic modulus (RDEM) of four different kinds of modified concrete under the special environment in the northwest of China was established using Grey residual Markov theory. Based on the available test data, modified values of the dynamic elastic modulus were obtained based on the Grey GM(1,1) model and the residual GM(1,1) model, combined with the Markov sign correction, and the dynamic elastic modulus of concrete was predicted. The computational analysis showed that the maximum relative error of the corrected dynamic elastic modulus was significantly reduced, from 1.599% to 0.270% for the BS2 group. The analysis error showed that the model was more adjusted to the concrete mixed with fly ash and mineral powder, and its calculation error was significantly lower than that of the rest of the groups. The analysis of the data for each group proved that the model could predict the loss of dynamic elastic modulus of the deterioration of the concrete effectively, as well as the number of cycles when the concrete reached the damaged state.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.14-21
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• 2011

Reliability means that a product maintains its initial quality and performance at certain period of time(time, distance, cycle etc) under given condition without failure. Given conditions include both environmental condition and operating condition. Environmental condition means common natural environment such as temperature, humidity, vibration, and working condition means artificial environment such as voltage, current load, install place, hours of use, which occurs during using the product. In the field of railway vehicles, although components of railway vehicles with reliability are the trend of mandatory as persisting period of railway vehicles is extended, using components of railway vehicles is insufficient for the practical reliability assessment. but the meaning of the first railway operating agnecy to acquire the parts in the field, the data suggest the reliability of products if you can and can show the reliability of modular units and modular units can provide the reliability of if you can present reliability of the entire system is thought to be here. In this study, lifespan of micro-switch for master controller is analyzed and prediction is performed based on its field data considering the special circumstances of railway vehicles operating agency, such as a large number of trains operates on the same line.

• Journal of the Korean Society of Systems Engineering
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• v.7 no.1
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• pp.57-69
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• 2011

Reliability means that a product maintains its initial quality and performance at certain period of time(time, distance, cycle etc) under given condition without failure. Given conditions include both environmental condition and operating condition. Environmental condition means common natural environment such as temperature, humidity, vibration, and working condition means artificial environment such as voltage, current load, install place, hours of use, which occurs during using the product. In the field of railway vehicles, although components of railway vehicles with reliability are the trend of mandatory as persisting period of railway vehicles is extended, using components of railway vehicles is insufficient for the practical reliability assessment. but the meaning of the first railway operating agency to acquire the parts in the field, the data suggest the reliability of products if you can and can show the reliability of modular units and modular units can provide the reliability of if you can present reliability of the entire system is thought to be here In this study, lifespan of micro-switch for master controller is analyzed and prediction is performed based on its field data considering the special circumstances of railway vehicles operating agency, such as a large number of trains operates on the same line.

• Journal of Internet of Things and Convergence
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• v.7 no.4
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• pp.9-14
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• 2021

In computing systems that require high reliability, the method of predicting the lifetime of a storage device is one of the important factors for system management because it can maximize usability as well as data protection. The life of a solid state drive (SSD) that has recently been used as a storage device in several storage systems is linked to the life of the NAND flash memory that constitutes it. Therefore, in a storage system configured using an SSD, a method of accurately and efficiently predicting the lifespan of a NAND flash memory is required. In this paper, a method for optimizing the lifetime prediction of a flash memory-based storage device using the frequency of NAND flash memory failure is proposed. For this, we design a cost matrix to collect the frequency of defects that occur when processing data in units of Drive Writes Per Day (DWPD). In addition, a method of predicting the remaining cost to the slope where the life-long finish occurs using the Gradient Descent method is proposed. Finally, we proved the excellence of the proposed idea when any defect occurs with simulation.