• Steel and Composite Structures
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• v.47 no.2
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• pp.185-201
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• 2023

Despite the high lateral stiffness and strength of the Concentrically Braced Frame (CBF), due to the buckling of its diagonal members, it is not a suitable system in high seismic regions. Among the offered methods to overcome the shortcoming, utilizing a metallic damper is considered as an appropriate idea to enhance the behavior of Concentrically Braced Frames (CBFs). Therefore, in this paper, an innovative steel damper is proposed, which is investigated experimentally and numerically. Moreover, a parametrical study was carried out to evaluate the effect of the mechanism (shear, shear-flexural, and flexural) considering buckling mode (elastic, inelastic, and plastic) on the behavior of the damper. Besides, the necessary formulas based on the parametrical study were presented to predict the behavior of the damper that they showed good agreement with finite element (FE) results. Both experimental and numerical results confirmed that dampers with the shear mechanism in all buckling modes have a better performance than other dampers. Accordingly, the FE results indicated that the shear damper has greater ultimate strength than the flexural damper by 32%, 31%, and 56%, respectively, for plates with elastic, inelastic, and plastic buckling modes. Also, the shear damper has a greater stiffness than the flexural damper by 43%, 26%, and 53%, respectively, for dampers with elastic, inelastic, and plastic buckling modes.

• Structural Engineering and Mechanics
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• v.87 no.5
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• pp.451-460
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• 2023

Recently, the use of smartphones for structural health monitoring in civil engineering has drawn increasing attention due to their rapid development and popularization. In this study, the structural responses and dynamic characteristics of a 421-m-tall skyscraper during the landfall of Typhoon Muifa are monitored using an iPhone 13. The measured building acceleration responses are first corrected by the resampling technique since the sampling rate of smartphone-based measurement is unstable. Then, based on the corrected building acceleration, the wind-induced responses (i.e., along-wind and across-wind responses) are investigated and the serviceability performance of the skyscraper is assessed. Next, the amplitude-dependency and time-varying structural dynamic characteristics of the monitored supertall building during Typhoon Muifa are investigated by employing the random decrement technique and Bayesian spectral density approach. Moreover, the estimated results during Muifa are further compared with those of previous studies on the monitored building to discuss its long-term time-varying structural dynamic characteristics. The paper aims to demonstrate the applicability and effectiveness of smartphones for structural health monitoring of high-rise buildings.

• Structural Engineering and Mechanics
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• v.87 no.6
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• pp.555-574
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• 2023

An efficient optimization algorithm and damage-sensitive objective function are two main components in optimization-based Finite Element Model Updating (FEMU). A suitable combination of these components can considerably affect damage detection accuracy. In this study, a new hybrid damage-sensitive objective function is proposed based on combining two different objection functions to detect the location and extent of damage in structures. The first one is based on Generalized Pseudo Modal Strain Energy (GPMSE), and the second is based on the element's Generalized Flexibility Matrix (GFM). Four well-known population-based metaheuristic algorithms are used to solve the problem and report the optimal solution as damage detection results. These algorithms consist of Cuckoo Search (CS), Teaching-Learning-Based Optimization (TLBO), Moth Flame Optimization (MFO), and Jaya. Three numerical examples and one experimental study are studied to illustrate the capability of the proposed method. The performance of the considered metaheuristics is also compared with each other to choose the most suitable optimizer in structural damage detection. The numerical examinations on truss and frame structures with considering the effects of measurement noise and availability of only the first few vibrating modes reveal the good performance of the proposed technique in identifying damage locations and their severities. Experimental examinations on a six-story shear building structure tested on a shake table also indicate that this method can be considered as a suitable technique for damage assessment of shear building structures.

• Advances in nano research
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• v.13 no.4
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• pp.369-378
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• 2022

Dynamic study of concrete plates under impact load is presented in this article. The main objective of this work is presenting a mathematical model for the concrete plates under the impact load. The concrete plate is reinforced by carbon nanoparticles which the effective material proprieties are obtained by mixture's rule. Impacts are assumed to occur normally over the top layer of the plate and the interaction between the impactor and the structure is simulated using a new equivalent three-degree-of-freedom (TDOF) spring-mass-damper (SMD) model. The structure is assumed viscoelastic based on Kelvin-Voigt model. Based on the classical plate theory (CPT), energy method and Hamilton's principle, the motion equations are derived. Applying DQM, the dynamic deflection and contact force of the structure are calculated numerically so that the effects of mass, velocity and height of the impactor, volume percent of nanoparticles, structural damping and geometrical parameters of structure are shown on the dynamic deflection and contact force. Results show that considering structural damping leads to lower dynamic deflection and contact force. In addition, increasing the volume percent of nanoparticles yields to decreases in the deflection.

• Steel and Composite Structures
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• v.45 no.4
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• pp.555-562
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• 2022

Improving the mechanical properties of concrete in the construction industry in order to increase resistance to dynamic and static loads is one of the essential topics for researchers. In this work, vibration analysis of elastic nanocomposite beams reinforced by nanoparticles based on mathematical model is presented. For modelling of the strucuture, sinusoidal shear deformation beam theory (SSDBT) is utilized. Mori-anak model model is utilized for obtaining the effective properties of the strucuture including agglomeration influences. Utilizing the energy method and Hamilton's principal, the motion equations are calculated. The frequency of the elastic nanocomposite beam is obtanied by analytical method. The aim of this work is investigating the effects of nanoparticles volume percent and agglomeration, length and thickness of the beam on the frequency of the structure. The results show that the with enhancing the nanoparticles volume percent, the frequency is increased. In addition, the water absorption of the concrete is presented in this article.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.21 no.3
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• pp.347-357
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• 2023

United States Nuclear Regulatory Commission (U.S. NRC) specifies regulations on obtaining licenses and describes the technical position on the average waste concentration, also known as Concentration Averaging and Encapsulation Branch Technical Position (CA BTP); CA BTP helps classify blendable waste and discrete items and address concentration averaging. The technical position details are reviewed and compared in a real environment in Korea. A few cases of concentration averaging based on the application of CA BTP to domestic radioactive waste are presented, and the feasibility of the application is assessed. The radioactive waste considered herein does not satisfy the Disposal Concentration Limit (DCL) of the second-phase disposal facility while applying the preliminary classification. However, if CA BTP is applied when the radioactive waste is mixed with other radioactive waste items in a large and heavy container, it can be disposed of at the second-phase disposal facility in Gyeongju Repository. To apply the CA BTP of the U.S. NRC, it is necessary to investigate the safety assessment conditions of the US and Korea.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.190-194
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• 2023

By looking the importance of communication, data delivery and access in various sectors including governmental, business and individual for any kind of data, it becomes mandatory to identify faults and flaws during cyber communication. To protect personal, governmental and business data from being misused from numerous advanced attacks, there is the need of cyber security. The information security provides massive protection to both the host machine as well as network. The learning methods are used for analyzing as well as preventing various attacks. Machine learning is one of the branch of Artificial Intelligence that plays a potential learning techniques to detect the cyber-attacks. In the proposed methodology, the Decision Tree (DT) which is also a kind of supervised learning model, is combined with the different cross-validation method to determine the accuracy and the execution time to identify the cyber-attacks from a very recent dataset of different network attack activities of network traffic in the UNSW-NB15 dataset. It is a hybrid method in which different types of attributes including Gini Index and Entropy of DT model has been implemented separately to identify the most accurate procedure to detect intrusion with respect to the execution time. The different DT methodologies including DT using Gini Index, DT using train-split method and DT using information entropy along with their respective subdivision such as using K-Fold validation, using Stratified K-Fold validation are implemented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.551-569
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• 2024

With the rapid development of electric vehicles (EVs) industry, EV charging service becomes more and more important. Especially, in the case of suddenly drop of air temperature or open holidays that large-scale EVs seeking for charging devices (CDs) in a short time. In such scenario, inefficient EV charging scheduling algorithm might lead to a bad service quality, for example, long queueing times for EVs and unreasonable idling time for charging devices. To deal with this issue, this paper propose a Deep-Q-Network (DQN) based two-stage scheduling method for the large-scale EVs charging service. Fine-grained states with two delicate neural networks are proposed to optimize the sequencing of EVs and charging station (CS) arrangement. Two efficient algorithms are presented to obtain the optimal EVs charging scheduling scheme for large-scale EVs charging demand. Three case studies show the superiority of our proposal, in terms of a high service quality (minimized average queuing time of EVs and maximized charging performance at both EV and CS sides) and achieve greater scheduling efficiency. The code and data are available at THE CODE AND DATA.

• Journal of Periodontal and Implant Science
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• v.53 no.5
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• pp.336-346
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• 2023

Purpose: The Korea Oral Biobank Network (KOBN) was established in 2021 as a branch of the Korea Biobank Network under the Korea Centers for Disease Control and Prevention to provide infrastructure for the collection, management, storage, and utilization of human bioresources from the oral cavity and associated clinical data for basic research and clinical studies. Methods: To address the need for the unification of the biobanking process, the KOBN organized the concept review for all the processes. Results: The KOBN established standard operating procedures for the collection, processing, and storage of oral samples. Conclusions: The importance of collecting high-quality bioresources to generate accurate and reproducible research results has always been emphasized. A standardized procedure is a basic prerequisite for implementing comprehensive quality management of biological resources and accurate data production.

• Archives of Pharmacal Research
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• v.27 no.4
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• pp.361-370
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• 2004

The discovery of insulin receptor substrate (IRS) proteins and their role to link cell surface receptors to the intracellular signaling cascades is a key step to understanding insulin and insulin-like growth factor (IGF) action. Moreover, IRS-proteins coordinate signals from the insulin and IGF receptor tyrosine kinases with those generated by proinflammatory cytokines and nutrients. The IRS2-branch of the insulin/IGF signaling cascade has an important role in both peripheral insulin response and pancreatic $\beta$-cell growth and function. Dysregulation of IRS2 signaling in mice causes the failure of compensatory hyperinsulinemia during peripheral insulin resistance. IRS protein signaling is down regulated by serine phosphorylation or protea-some-mediated degradation, which might be an important mechanism of insulin resistance during acute injury and infection, or chronic stress associated with aging or obesity. Under-standing the regulation and signaling by IRS1 and IRS2 in cell growth, metabolism and survival will reveal new strategies to prevent or cure diabetes and other metabolic diseases.