• Earthquakes and Structures
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• v.8 no.5
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• pp.995-1016
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• 2015

The reliability or the safety index is a measure of how far a structure is from the state of collapse. Also it defined as the probability that a structure will not fail in its lifetime. Having any increase in the reliability index is typically interpreted as increasing in the safety of structures. On the other hand most of researchers acknowledged that one of the most effective means of increasing both the reliability and the safety of structures is to increase the structural redundancy. They also acknowledged that increasing the number of vertical seismic framing will make structural system more reliable and safer against stochastic events such as earthquakes. In this paper the reliability index and the behavior factor of a numbers of three dimensional RC moment resisting frames with the same story area, equal lateral resistant as well as different redundancy has been evaluated numerically using both deterministic and probabilistic approaches. Study on the reliability index and the behavior factor in the case study models of this research illustrated that the changes of these two factors do not have always the same manner due to the increasing of the structural redundancy. In some cases, structures with larger reliability index have smaller behavior factor. Also assuming the same ultimate lateral resistance of structures which causes an increase to a certain level of redundancy can enhance behavior factor of structures. However any further increase in the redundancy of that certain level might decrease the behavior factor. Furthermore, the results of this study illustrate that concerning any increase in the structural redundancy will make the reliability index of structure to be larger.

• The korean journal of orthodontics
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• v.53 no.2
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• pp.116-124
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• 2023

Objective: The absence of a guideline to refer to developing malocclusions appropriately, may be a contributing factor to the inadequacy of timely interceptive orthodontics provision. This study aimed to develop and validate a new orthodontic grading and referral index to be used by dental frontliners to prioritize the orthodontic referral of developing malocclusion in children based on its severity. Methods: A cross-sectional study involving clinical assessment with 413 schoolchildren aged between 8.1 and 11.9 years was conducted in 2018. All the presenting malocclusion was listed and graded based on a few dental guidelines to produce the draft index. The validity and reliability of the draft index were tested using twenty study models. Face and content validation was carried out using the content validation index and Modified Kappa Statistics. Results: Fourteen dental and occlusal anomalies were identified as components of malocclusion and three grades of referral (monitor, standard, urgent) were included in the final index. The scale-level content validity index average value of 0.86 and 0.87 was obtained for content and face validation, respectively. There was moderate to excellent agreement in the Modified Kappa Statistics for both validations. Excellent inter- and intra-assessor agreement was obtained. The new index displayed valid and reliable scores. Conclusions: The Index for Interceptive Orthodontics Referral was developed and validated for the dental frontliners to identify and prioritize the developing malocclusion in children based on its severity and refer for orthodontic consultation to increase the possibility for interceptive orthodontics.

• Journal of the Korean Geotechnical Society
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• v.20 no.5
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• pp.17-25
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• 2004

The flat dilatometer test (DMT) is a geotechnical tool to estimate in-situ properties of various types of ground materials. The undrained shear strength is known to be the most reliable and useful parameter obtained by DMT. However, the existing relationships which were established for other local deposits depend on the regional geotechnical characteristics. In addition, the flat dilatometer test results have been interpreted using three intermediate indices - material index $(I_D)$, horizontal stress index $(K_D)$, and dilatometer modulus (E$_{D}$) and the undrained shear strength has been estimated merely using the horizontal stress index $(K_D)$. In this paper, the applicability of the flat dilatometer to Korean soft clay deposit has been investigated. Then an artificial neural network was developed to evaluate the undrained shear strength by DMT and the ANN, based on the $p_0, p_1, p_2, {\sigma '}_v$ and porewater pressure. The ANN which adopts the back-propagation algorithm was trained based on the DMT data obtained from Korean soft clay. To investigate the feasibility of ANN model, the prediction results obtained from data which were not used to train the ANN and those obtained from existing relationships were compared.

• Proceedings of the Korean Geotechical Society Conference
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• 2004.03b
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• pp.154-161
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• 2004

The flat dilatometer test(DMT) is a geotechnical tool to estimate in-situ properties of various types of ground materials. The undrained shear strength is known to be the most reliable and useful parameter obtained by DMT. However, the existing relationships which were established for other local deposits depend on the regional geotechnical characteristics. In addition, the flat dilatometer test results have been interpreted using three intermediate indicesmaterial index($I_p$), horizontal stres index($K_p$), and dilatometer modulus($E_p$) and the undrained shear strength is estimated only by using the horizontal stress index($K_D$). In this paper, an artificial neural network was developed to evaluate the undrained shear strength by DMT and the ANN, based on the $p_0,\;p_1,\;p_2,\;{\sigma}'_v_0$, and porewater pressure. The ANN which adopts the back-propagation algorithm was trained based on the DMT data obtained from Korean soft clay. To investigate the feasibility of ANN model, the prediction results obtained from data which were not used to train the ANN and those obtained from existing relationships were compared.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.2
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• pp.387-395
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• 2013

It is important to collect reliable measured data for proper bridge health monitoring. However, in reality incomplete and unreliable data may be acquired due to sensor problems and environmental effects. In case of sensor malfunction, parts of measured data are missing and thus health monitoring cannot be carried out reliably. Due to environmental effects such as temperature variation, dynamic characteristics of natural frequencies may change as if the structure is damaged. The paper proposes a systematic procedure of data processing and data analysis for reliable structural health monitoring. Also, it applies the Mahalanobis distance as a health index computed statistically using revised data. The proposed procedure has been examined using numerically simulated data from a truss structure and then applied to a set of field data measured from Seohae cable-stayed bridge.

• Structural Engineering and Mechanics
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• v.78 no.1
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• pp.53-66
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• 2021

The determination of the damage index to reveal the performance level of a structure can constitute the seismic risk generalization approach based on the parametric analysis. This study implemented this concept to one kind of civil engineering structure that is the concrete gravity dam. Different cases of the structure exhibit their individual responses, which constitute different considerations. Therefore, this approach allows the parametric study of concrete as well as soil for evaluating the seismic nature in the generalized case. To ensure that the target algorithm applicable to most of the concrete gravity dams, a very simple procedure has been considered. In order to develop a correlated algorithm (by response surface methodology; RSM) between the ground motion and the structural property, randomized sampling was adopted through a stochastic method called half-fractional central composite design. The responses in the case of fluid-foundation-dam interaction (FFDI) make it more reliable by introducing the foundation as being bounded by infinite elements. To evaluate the seismic generalization of FFDI models, incremental dynamic analysis (IDA) was carried out under the impacts of various earthquake records, which have been selected from the Pacific Earthquake Engineering Research Center data. Here, the displacement-based damage indexed fragility curves have been generated to show the variation in the seismic pattern of the dam. The responses to the sensitivity analysis of the various parameters presented here are the most effective controlling factors for the concrete gravity dam. Finally, to establish the accuracy of the proposed approach, reliable verification was adopted in this study.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.141-141
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• 2022

Drought is a global phenomenon that affects almost all landscapes and causes major damages. Due to non-linear nature of contributing factors, drought occurrence and its severity is characterized as stochastic in nature. Early warning of impending drought can aid in the development of drought mitigation strategies and measures. Thus, drought forecasting is crucial in the planning and management of water resource systems. The primary objective of this study is to make improvement is existing drought forecasting techniques. Therefore, we proposed an improved version of Seasonal Autoregressive Integrated Moving Average (SARIMA) model (MD-SARIMA) for reliable drought forecasting with three years lead time. In this study, we selected four watersheds of Han River basin in South Korea to validate the performance of MD-SARIMA model. The meteorological data from 8 rain gauge stations were collected for the period 1973-2016 and converted into watershed scale using Thiessen's polygon method. The Standardized Precipitation Index (SPI) was employed to represent the meteorological drought at seasonal (3-month) time scale. The performance of MD-SARIMA model was compared with existing models such as Seasonal Naive Bayes (SNB) model, Exponential Smoothing (ES) model, Trigonometric seasonality, Box-Cox transformation, ARMA errors, Trend and Seasonal components (TBATS) model, and SARIMA model. The results showed that all the models were able to forecast drought, but the performance of MD-SARIMA was robust then other statistical models with Wilmott Index (WI) = 0.86, Mean Absolute Error (MAE) = 0.66, and Root mean square error (RMSE) = 0.80 for 36 months lead time forecast. The outcomes of this study indicated that the MD-SARIMA model can be utilized for drought forecasting.

• Journal of Technology Innovation
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• v.19 no.3
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• pp.85-114
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• 2011

This paper aims at developing a new index that represents the Korean new growth industries, which is named the Korea Future Technology Index(KOFTI). The KOFTI is designed to provide a reliable and econometric index based on which the Korean government searches for new growth engines. The KOFTI is composed of three individual indexes such as the Economic Impact Index, the Future Strategy Index, and the Technological Influence Index. The KOFTI is applied for 62 star brands, which have been promoted by the Korean government for the korean future industrial competitiveness. The top 13 leading industries are drawn from the calculation of the KOFTI for 62 star brands.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6C
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• pp.421-429
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• 2006

This study was undertaken to develop an analysis model representing a reliable estimation of rigidity of Korean soft clay using an artificial neural network (ANN). Data for the model development were obtained through a laboratory study, and were used for training and verification. The coefficient of correlation between the measured and predicted data using the developed model was relatively high. It demonstrates the potential application of ANN for the reliable estimation of Korean soft clay rigidity while past attempts at building such a mathematical model have proved difficult.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.5
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• pp.309-318
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• 1987

In the on-line security analysis of power system, Automatic Contingency Selection (ACS) is commonly used to reduce the number of contingency cases which will be evaluated in detail. This paper describes a fast and reliable ACS method which adopts DC load flow in conjunction with compensation theorem to improve execution time, and applies severity performance index, divided on each limit level for considering overload rate, to make reliable contingency ranking. The method has been tested in IEEE 25 bus system and KEPCO 130 bus actual power system. The results of these tests verify its superiority to both the execution time and reliability, and illustrate its effectiveness for the practical use.