• The Journal of Korea Robotics Society
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• v.11 no.4
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• pp.277-284
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• 2016

A new prediction scheme has been proposed for the robust teleoperation in a non-visible environment. The positioning error caused by the time delay in the non-visible environment has been compensated for by the Smith predictor and the sensory data have been estimated by the Grey model. The Smith predictor is effective for the compensation of the positioning error caused by the time delay with a precise system model. Therefore the dynamic model of a mobile robot has been used in this research. To minimize the unstable and erroneous states caused by the time delay, the estimated sensor data have been sent to the operator. Through simulations, the possibility of compensating the errors caused by the time delay has been verified using the Smith predictor. Also the estimation reliability of the measurement data has been demonstrated. Robust teleoperations in a non-visible environment have been performed with a mobile robot to avoid the obstacles effective to go to the target position by the proposed prediction scheme which combines the Smith predictor and the Grey model. Even though the human operator is involved in the teleoperation loop, the compensation effects have been clearly demonstrated.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.453-456
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• 2022

The role of the power grid is to ensure stable power supply. It is necessary to take various measures to prepare for unstable situations without notice. After identifying the relationship between features through exploratory data analysis using weather data, a machine learning based energy production prediction model is modeled. In this study, the prediction reliability was increased by extracting the features that affect energy production prediction using principal component analysis and then applying it to the machine learning model. By using the proposed model to predict the production energy for a specific period and compare it with the actual production value at that time, the performance of the energy production prediction applying the principal component analysis was confirmed.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1993.10a
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• pp.240-247
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• 1993

The precise prediction of reserved carrying capacity of bridge as a system is extremely difficult especially when the bridges are highly redundant and significantly deteriorated or damaged. This paper is intended to propose a new approach for the evaluation of reserved system carrying capacity of bridges in terms of equivalent system-strength, which may be defined as a bridge system-strength corresponding to the system reliability of the bridge. This can be derived from an inverse process based on the concept of FOSM form of system reliability index. It may be emphasized that this approach is very useful for the evaluation of the deterministic system redundancy and reserve strength which are measured in terms of either probabilistic system redundancy factor and reserve factor or deterministic system redundancy factor and reserve factor. The system reliability of bridges is formulated as a parallel-series model obtained from the FAM(Failure Mode Approach) based on the major failure mechanisms. AFOSM and IST methods are used for the reliability analysis of the proposed models. The proposed approach and method for the system redundancy and reserve safety/strength are applied to the safety assessment of actual RC and steel box-girder bridges. The results of the evaluation of reserved system safety or bridge system-strength in terms of the system redundancy and the system safety/strength are significantly different from those of element reliability-based or conventional methods.

• Proceedings of the Korean Reliability Society Conference
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• 2006.05a
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• pp.116-125
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• 2006

Piston assemblies, which are key components of hydraulic high pressure pumps & motors, are major failure products operating at high pressure and high speed, and the main failure mode is wearout of the shoe surface. To predict the actual life of piston assemblies. we require to find out the most sensitive parameters and establish related empirical formula. In this study, we analyzed the life of piston and shoe assemblies in accordance with variation of speed, pressure, and temperature to reduce the life test time, then analyzed the result of combined accelerated life test which is applied by high speed, speed pressure, and high temperature simultaneously, and finally developed combined accelerated life test model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.83-104
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• 2011

Mobile grid is a combination of grid computing and mobile computing to build grid systems in a wireless mobile environment. The development of network technology is assisting in realizing mobile grid. Mobile grid based on established grid infrastructures needs effective resource management and reliable job scheduling because mobile grid utilizes not only static grid resources but also dynamic grid resources with mobility. However, mobile devices are considered as unavailable resources in traditional grids. Mobile resources should be integrated into existing grid sites. Therefore, this paper presents a mobile grid middleware interconnecting existing grid infrastructures with mobile resources and a mobile service agent installed on the mobile resources. This paper also proposes a mobile resource reliability-based job scheduling model in order to overcome the unreliability of wireless mobile devices and guarantee stable and reliable job processing. In the proposed job scheduling model, the mobile service agent calculates the mobile resource reliability of each resource by using diverse reliability metrics and predicts it. The mobile grid middleware allocated jobs to mobile resources by predicted mobile resource reliability. We implemented a simulation model that simplifies various functions of the proposed job scheduling model by using the DEVS (Discrete Event System Specification) which is the formalism for modeling and analyzing a general system. We also conducted diverse experiments for performance evaluation. Experimental results demonstrate that the proposed model can assist in improving the performance of mobile grid in comparison with existing job scheduling models.

• Proceedings of the Korean Reliability Society Conference
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• 2005.06a
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• pp.69-73
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• 2005

The failure of geogrids used for soil reinforcement application can be defined as an excessive creep strain which causes the collapse of slopes and embankments. Accordingly, the lifetime is evaluated as a time to reach the excessive creep strain using two accelerated creep testing methods, time-temperature superposition(TTS) and stepped isothermal methods(SIM). TTS is a well-accepted acceleration method to evaluate creep behavior of polymeric materials, while SIM was developed in the last ten years mainly to shorten testing time and minimize the uncertainty associated with inherent variability of multi-specimen tests. The SIM test is usually performed using single rib of geogrids for temperature steps of $14^{\circ}C$ and a dwell time of 10,000 seconds. However, for multi-ribs of geogrids, the applicability of the SIM has not been well established. In this study, the creep behaviors are evaluated using multi-ribs of polyester geogrids using SIM and TTS creep procedures and the newly designed test equipment. Then the lifetime of geogrids are predicted by analyzing the failure times to reach the excessive creep strains through reliability analysis.

• Korean Journal of Metals and Materials
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• v.50 no.10
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• pp.721-728
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• 2012

This paper evaluates the reliability of creep rupture life under service conditions of Alloy 617, which is considered as one of the candidate materials for use in a very high temperature reactor (VHTR) system. A Z-parameter, which represents the deviation of creep rupture data from the master curve, was used for the reliability analysis of the creep rupture data of Alloy 617. A Service-condition Creep Rupture Interference (SCRI) model, which can consider both the scattering of the creep rupture data and the fluctuations of temperature and stress under any service conditions, was also used for evaluating the reliability of creep rupture life. The statistical analysis showed that the scattering of creep rupture data based on Z-parameter was supported by normal distribution. The values of reliability decreased rapidly with increasing amplitudes of temperature and stress fluctuations. The results established that the reliability decreased with an increasing service time.

• Journal of the Korean Society of Safety
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• v.38 no.5
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• pp.43-50
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• 2023

With the advent of industrialization, consumers and end-users demand more reliable products. Meeting these demands requires a comprehensive approach, involving tasks such as market information collection, planning, reliable raw material procurement, accurate reliability design, and prediction, including various reliability tests. Moreover, this encompasses aspects like reliability management during manufacturing, operational maintenance, and systematic failure information collection, interpretation, and feedback. Improving product reliability requires prioritizing it from the initial development stage. Failure mode and effect analysis (FMEA) is a widely used method to increase product reliability. In this study, we reanalyzed using the FMEA method and proposed an improved method. Domestic railways lack an accurate measurement method or system for maintenance, so maintenance decisions rely on the opinions of experienced personnel, based on their experience with past faults. However, the current selection method is flawed as it relies on human experience and memory capacity, which are limited and ineffective. Therefore, in this study, we further specify qualitative contents to systematically accumulate failure modes based on the Failure Modes Table and create a standardized form based on the Master FMEA form to newly systematize it.

• The KIPS Transactions:PartD
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• v.8D no.2
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• pp.175-180
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• 2001

This paper presents the optimal fraction of validation set to obtain a prediction accuracy of software failure count or failure time in the future by a neuro-fuzzy system. Given a fixed amount of training data, the most popular effective approach to avoiding underfitting and overfitting is early stopping, and hence getting optimal generalization. But there is unresolved practical issues : How many data do you assign to the training and validation set\ulcorner Rules of thumb abound, the solution is acquired by trial-and-error and we spend long time in this method. For the sake of optimal fraction of validation set, the variant specific fraction for the validation set be provided. It shows that minimal fraction of the validation data set is sufficient to achieve good next-step prediction. This result can be considered as a practical guideline in a prediction of software reliability by neuro-fuzzy system.

• The Journal of the Korea Contents Association
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• v.15 no.8
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• pp.24-36
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• 2015

Recently, interests in detecting hot topics have been significantly growing as it becomes important to find out and analyze meaningful information from the large amount of data which flows in from social network services. Since it deals with a number of random writings that are not confirmed in advance due to the characteristics of SNS, there is a problem that the reliability of the results declines when hot topics are predicted from the writings. To solve such a problem, this paper proposes a high reliable hot topic prediction scheme considering user influences in social networks. The proposed scheme extracts a set of keywords with hot issues instantly through the modified TF-IDF algorithm based on Twitter. It improves the reliability of the results of hot topic prediction by giving weights of user influences to the tweets. To show the superiority of the proposed scheme, we compare it with the existing scheme through performance evaluation. Our experimental results show that our proposed method has improved precision and recall compared to the existing method.