• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.2 s.42
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• pp.7-15
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• 2005

Numerical analysis model is proposed to predict the dynamic behavior of a single-degree-of-freedom structure that is equipped with hybrid base isolation system. Hybrid base isolation system is composed of friction pendulum systems (FPS) and a magnetorheological (MR) damper. A neuro-fuzzy model is used to represent dynamic behavior of the MR damper. Fuzzy model of the MR damper is trained by ANFIS (Adaptive Neuro-Fuzzy Inference System) using various displacement, velocity, and voltage combinations that are obtained from a series of performance tests. Modelling of the FPS is carried out with a nonlinear analytical equation that is derived in this study and neuro-fuzzy training. Fuzzy logic controller is employed to control the command voltage that is sent to MR damper. The dynamic responses of experimental structure subjected to various earthquake excitations are compared with numerically simulated results using neuro-fuzzy modeling method. Numerical simulation using neuro-fuzzy models of the MR damper and FPS predict response of the hybrid base isolation system very well.

• Journal of the Korean Ceramic Society
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• v.41 no.12 s.271
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• pp.873-879
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• 2004

In all major industries ranging from powder industries and advanced ceramics, to the food and pharmaceutical manufacture powder industries, the main production process is the spray dryers. In this paper, a systematic approach is used and six rules are obtained for the basis of the fuzzy model. A fuzzy model is based on the past behavior of the target system and expected to be able to reproduce the behavior of the target system. The output of the developed fuzzy model shows, graphically and statistically, a high level of face validity. Therefore, it is concluded that the developed fuzzy model mimics the actual process and can be considered, with confidence, as a reliable model to study, analyze, and improve the existing process.

• Journal of Educational Research in Mathematics
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• v.9 no.2
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• pp.459-471
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• 1999

This study is to develop a mathematics assessment framework based on the mathematics assessment framework and content strands suggested by KEDI, NCTM, NAEP, TIMSS, Oregon State, New Zealand. According to the literature review, there has been more emphasis that students themselves 'communicate' what they 'understood' and how they 'thought' during the situation of 'solving problems'. As a result, communication ability is considered one of the most important factors in assessment situation, which always accompany the abilities of understanding, thinking, problem-solving, etc. In conclusion, the framework related to mathematical knowledge consists of content and behavior domains. The content domain is categorized into 6 content areas of the 7th mathematics curriculum, and the behavior domain is divided into computation, understanding, inference, problem-solving, and communication.

• Computers and Concrete
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• v.21 no.6
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• pp.649-659
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• 2018

Adaptive neuro-fuzzy inference systems (ANFIS) can be efficient in modelling non-linear, complex and ambiguous behavior of cement-based materials undergoing combined damage factors of different forms (physical and chemical). The current work investigates the use of ANFIS to model the behavior (time of failure (TF)) of a wide range of concrete mixtures made with different types of cement (ordinary and portland limestone cement (PLC)) without or with supplementary cementitious materials (SCMs: fly ash and nanosilica) under various exposure regimes with the most widely used chloride-based de-icing salts (individual and combined). The results show that predictions of the ANFIS model were rational and accurate, with marginal errors not exceeding 3%. In addition, sensitivity analyses of physical penetrability (magnitude of intruding chloride) of concrete, amount of aluminate and interground limestone in cement and content of portlandite in the binder showed that the predictive trends of the model had good agreement with experimental results. Thus, this model may be reliably used to project the deterioration of customized concrete mixtures exposed to such aggressive conditions.

• Journal of information and communication convergence engineering
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• v.19 no.1
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• pp.29-35
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• 2021

While the population of pet dogs and pet-related markets are increasing, there is no convenient and reliable tool for pet health monitoring for pet owners/caregivers. In this paper, we propose a mobile platform-based pre-diagnosis system that pet owners can use for pre-diagnosis and obtaining information on coping strategies based on their observations of the pet dog's abnormal behavior. The proposed system constructs symptom-disease association databases for 100 frequently observed diseases under veterinarian guidance. Then, we apply the possibilistic fuzzy C-means algorithm to form the "probable disease" set and the "doubtable disease" set from the database. In the experiment, we found that the proposed system found almost all diseases correctly, with an average of 4.5 input symptoms and outputs 1.5 probable and one doubtable disease on average. The utility of this system is to alert the owner's attention to the pet dog's abnormal behavior and obtain an appropriate coping strategy before consult a veterinarian.

• Journal of Korean Academy of Nursing
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• v.39 no.4
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• pp.480-489
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• 2009

Purpose: The purpose of this study was to identify the factors which influence health-related quality of life (HRQoL) in Korean Medicaid beneficiaries. The relationships among sociodemographic factors, health status, health behavior, and HRQoL were analyzed. Methods: Data from the 2007 survey on Health Services Use and Health Status of Medicaid Beneficiaries conducted by the Ministry for Health Welfare and Family Affairs were examined. To analyze the sample survey data, descriptive statistics, correlation and hierarchical multiple survey regression analysis with SAS 9.1.3 package were used with SURVEYMEANS and SURVEYREG procedures, which incorporate the sample design into the analyses in order to make statistically valid inference for the whole Medicaid population. Results: The HRQoL correlated with limitations in Activities of Daily Living (ADL) (r=-.509, p<.001), stress (r=-.387, p<.001), depression (r=-.385, p<.001), alcohol consumption (r=.216, p<.001), and exercise (r=.293, p<.001). Significant factors that affect HRQoL of Medicaid beneficiaries were gender, region, limitations in ADL, stress, depression, alcohol consumption, and regular exercise. These variables explained 44.6% of HRQoL (F= 215.00, p<.001). Conclusion: The results indicate that to improve the HRQoL of Medicaid beneficiaries it is important to develop nursing intervention programs that focus on psychological health and health behavior and to give consideration to differences in gender and region.

• Steel and Composite Structures
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• v.43 no.5
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• pp.625-637
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• 2022

Axial compression capacity (P_u) is a significant yet complex parameter of concrete-filled steel tube (CFST) columns. This study offers a novel ensemble tool, adaptive neuro-fuzzy inference system (ANFIS) supervised by equilibrium optimization (EO), for accurately predicting this parameter. Moreover, grey wolf optimization (GWO) and Harris hawk optimizer (HHO) are considered as comparative supervisors. The used data is taken from earlier literature provided by finite element analysis. ANFIS is trained by several population sizes of the EO, GWO, and HHO to detect the best configurations. At a glance, the results showed the competency of such ensembles for learning and reproducing the P_u behavior. In details, respective mean absolute errors along with correlation values of 4.1809% and 0.99564, 10.5947% and 0.98006, and 4.8947% and 0.99462 obtained for the EO-ANFIS, GWO-ANFIS, and HHO-ANFIS, respectively, indicated that the proposed EO-ANFIS can analyze and predict the behavior of CFST columns with the highest accuracy. Considering both time and accuracy, the EO provides the most efficient optimization of ANFIS and can be a nice substitute for experimental approaches.

• Journal of KIISE:Software and Applications
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• v.36 no.2
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• pp.144-152
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• 2009

To provide intelligent service in mobile environment, it needs to estimate user's intention or requirement, through analyzing context information of end-users such as preference or behavior patterns. In this paper, we infer context information from uncertain log stored in mobile device. And we propose the inference method of end-user's behavior to match context information with service, and the proposed method is based on context-tree. We adopt bayesian probabilistic method to infer uncertain context information effectively, and the context-tree is constructed to utilize non-numerical context which is hard to handled with mathematical method. And we verify utility of proposed method by appling the method to intelligent phone book service.

• Structural Engineering and Mechanics
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• v.82 no.4
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• pp.445-458
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• 2022

Some of the control systems used in engineering structures that use sensors and decision systems have some time delay reducing efficiency of the control system or even might make it unstable. In this research, in addition to considering the effect of the time delay in vibration control process, predictive control is used to compensate the time delay. A semi-active vibration control approach with the help of magneto-rheological dampers is implemented. In addition to using fuzzy inference system to determine the appropriate control voltage for MR damper, structural behavior prediction system and specifying future responses are also used such that the time delays occurring within control process are overcome. For this purpose, determination of prediction horizon is conducted for one, five, and ten steps ahead for single degree of freedom structures with periods ranging from 0.1 to 4 seconds, subjected to twenty earthquake excitations. The amount of time delay applied to the control system is 0.1 seconds. The obtained results indicate that for 0.1 second time delay, average prediction error values compared to the case without time delay is 3.47 percent. Having 0.1 second time delay in a semi-active control system reduces its efficiency by 11.46 percent; while after providing the control system with structure behavior prediction, the difference in the results for the control system without time delay is just 1.35 percent on average; indicating a 10.11 percent performance improvement for the control system.

• Journal of the Korea Society for Simulation
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• v.20 no.3
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• pp.111-117
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• 2011

This paper suggests the passenger model considered evacuation behavioral characteristics on the passenger ship fire using a rules-based agent technique. The existing evacuation simulation system was modeled only passenger speed. The speed-based model considered passenger's physical characteristics, so it couldn't consider evacuation behavioral characteristics. For solving this problem, we modeled the passenger model using a rule-based agent applied evacuation behavioral characteristics. The rule-based agent consists of knowledge base and inference engine. In knowledge base, we represented evacuation behavioral characteristics, and chose the examples of the evacuation behavioral characteristics to show various patterns of behavior. And we simulated in the IMO MSC/Circ.1238 example 8 and we proved the simulation results could represent variety patterns of human behavior.