• Earthquakes and Structures
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• v.9 no.2
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• pp.375-390
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• 2015

Staircase is a vertical transportation element commonly used in every multistoried structure. Inclined flights of staircase are usually casted monolithically with RC frame. The structural configuration of stairs generally introduces discontinuities into the typical regular reinforced concrete frame composed of beams and columns. Inclined position of flight transfers both vertical as well as horizontal forces in the frame. Under lateral loading, staircase in a multistory RC frame building develops truss action creating a local stiffening effect. In case of seismic event the stiff area around staircase attracts larger force. Therefore, special attention is required while modeling and analyzing the building with staircase. However, in general design practice, designers usually ignore the staircase while modeling either due to ignorance or to avoid complexity. A numerical study has been conducted to examine the effect of ignoring staircase in modeling and design of RC frame buildings while they are really present in structure, may be at different locations. Linear dynamic analysis is performed on nine separate building models to evaluate influence of staircase on dynamic characteristics of building, followed by nonlinear static analysis on the same models to access their seismic performance. It is observed that effect of ignoring staircase in modeling is severe and leads to unsafe structure. Effect of location and orientation of staircase is also important in determining seismic performance of RC frame buildings.

• Cross-Cultural Studies
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• v.26
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• pp.73-94
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• 2012

In the present context of systemic global crisis, this paper focuses on a sustainable society. Throughout the World there are vast members of the unemployes. A secure job lasting a lifetime has become more and more rare. Nowadays majority of jobs are part-time or temporary. $Andr{\acute{e}}$ Gorz found a solution in a policy of the progessive reduction in labor time. This is the potential which automated production opens up for a culture society. Nevertheless, Gorz's proposal is based on utopion ideals. This paper focuses on a dynamic force for a culture society, especially art, learning and the third sector. Adrienne Goehler underlines that a culture in the broad sense of the word produces economical and social productivity. In this connection Goehler give attention to 'Cultrual Creatives' and the Creative Class. Cultural creatives are comprised of people who have participated in the process of creating a new culture with enlightened creativity. The Creative Class is a class of workers whose job is to create economic growth through innovation. Creativity is important for a sustainable society. Gore and Rifkin both come close to the ecological thinking. Gore claims that ecosystem of nature have a self-organizing capacity. In this context tried to prove this article that ecosystem is closely connected with a creative environment.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.1
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• pp.49-59
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• 2019

Generative adversarial networks(GANs) have received great attention in the machine learning field for their capacity to model high-dimensional and complex data distribution implicitly and generate new data samples from the model distribution. This paper investigates the model training methodology, architecture, and various applications of generative adversarial networks. Experimental evaluation is also conducted for generating synthetic image dataset for defense using two types of GANs. The first one is for military image generation utilizing the deep convolutional generative adversarial networks(DCGAN). The other is for visible-to-infrared image translation utilizing the cycle-consistent generative adversarial networks(CycleGAN). Each model can yield a great diversity of high-fidelity synthetic images compared to training ones. This result opens up the possibility of using inexpensive synthetic images for training neural networks while avoiding the enormous expense of collecting large amounts of hand-annotated real dataset.

• BioChip Journal
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• v.12 no.4
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• pp.268-279
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• 2018

Flower-shaped organic-inorganic hybrid nanostructures, termed nanoflowers, have received considerable recent attention as they possess greatly enhanced activity, stability, durability, and even selectivity of entrapped organic biomolecules, which are much better than those from the conventional methods. They can be synthesized simply via co-incubation of organic and inorganic components in aqueous buffer at room temperature and yield hierarchical nanostructures with large surface-to-volume ratios, allowing for low-cost production by easy scale-up, as well as the high loading capacity of biomolecules without severe mass transfer limitations. Since a pioneering study reported on hybrid nanoflowers prepared with protein and copper sulfate, many other organic and inorganic components, which endow nanoflowers with diverse functionalities, have been employed. Thanks to these features, they have been applied in a diverse range of areas, including biosensors and biocatalysis. To highlight the progress of research on organic-inorganic hybrid nanoflowers, this review discusses their synthetic methods and mechanisms, structural and biological characteristics, as well as recent representative applications. Current challenges and future directions toward the design and development of multi-functional nanoflowers for their widespread utilization in biotechnology are also discussed.

• Structural Engineering and Mechanics
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• v.68 no.6
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• pp.677-689
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• 2018

Residual deformation is a crucial index that should be paid special attention in the performance-based seismic analyses of reinforced concrete (RC) structures. Owing to their superior re-centering capacity under earthquake excitations, the post-tensioned self-centering (PTSC) RC frames have been proposed and developed for engineering application during the past few decades. This paper presents a comprehensive assessment on the seismic fragility of a PTSC frame by simultaneously considering maximum and residual deformations. Bivariate limit states are defined according to the pushover analyses for maximum deformations and empirical judgments for residual deformations. Incremental Dynamic Analyses (IDA) are conducted to derive the probability of exceeding predefined limit states at specific ground motion intensities. Seismic performance of the PTSC frame is compared with that of a conventional monolithic RC frame. The results show that, taking a synthetical consideration of maximum and residual deformations, the PTSC frame surpasses the monolithic frame in resisting most damage states, but is more vulnerable to ground motions with large intensities.

• Membrane and Water Treatment
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• v.10 no.6
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• pp.405-415
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• 2019

Microcystins (MCs) are toxins produced by cyanobacteria causing a major environmental threat to water resources worldwide. Although several MCs have been reported in previous studies, microcystin-LR (m-LR) has been extensively studied as it is highly toxic. Among the several techniques employed for the removal of this toxin, adsorption with AC has been extensively studied. AC has gained wide attention as an effective adsorbent of m-LR due to its ubiquity, high sorption capacity, cost effectiveness and renewability. In this review, the adsorption of m-LR onto AC was evaluated using the information available in existing scientific literature. The effects of the pore volume and surface chemistry of AC on the adsorption of m-LR considering the structural and chemical properties of ACs were also discussed. Furthermore, we identified the parameters that influence adsorption, including natural organic matter (NOM), pH, and ionic strength during the m-LR adsorption process. The effect of these parameters on MCs adsorption onto AC from previous studied is compiled and highlighted. This review may provide new insights into future activated carbon-m-LR adsorption research, and broaden its application prospects.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.173-178
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• 2020

As the fourth industrial revolution, in which people, objects, and information are connected as one, various fields such as smart energy, smart cities, artificial intelligence, the Internet of Things, unmanned cars, and robot industries are becoming the mainstream, drawing attention to big data. Among them, Smart Grid is a technology that maximizes energy efficiency by converging information and communication technologies into the power grid to establish a smart grid that can know electricity usage, supply volume, and power line conditions. Smart meters are equient that monitors and communicates power usage. We start with the goal of building a virtual smart grid and constructing a virtual environment in which real-time data is generated to accommodate large volumes of data that are small in capacity but regularly generated. A major role is given in creating a software/hardware architecture deployment environment suitable for the system for test operations. It is necessary to identify the advantages and disadvantages of the software according to the characteristics of the collected data and select sub-projects suitable for the purpose. The collected data was collected/loaded/processed/analyzed by the Hadoop ecosystem-based big data platform, and used to predict power demand through deep learning.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.33 no.12
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• pp.29-36
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• 2017

A recent global trend in the increase of earthquake-related disasters has become so frequent as to cause various damages to a wide range of mid- to high-rise buildings. Particularly, more attention is being paid to the effect of horizontal load in high-rise buildings not only on the key structural elements of the structures, but also on the possibility of the secondary damages to them due to the failure of exterior panels, which are non-structural elements, but such damages are difficult to cope with as they may be caused by unexpected changes. The present study examined exterior panels using moving clips to prevent such secondary damages on the non-structural elements and analyzed the structural performance of these exterior panels through the finite element analysis and the shaking table test. The analysis results showed that the exterior panels using moving clips satisfied the structural performance against the allowable story drift of KBC2009 and the safety of the exterior panels was verified by the shake table test.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2668-2717
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• 2021

Demands for high-speed wireless data services grow rapidly. It is a big challenge to increasing the network capacity operating on licensed spectrum resources. Unlicensed spectrum cellular networks have been proposed as a solution in response to severe spectrum shortage. Licensed Assisted Access (LAA) was standardized by 3GPP, aiming to deliver data services through unlicensed 5 GHz spectrum. Furthermore, the 3GPP proposed 5G New Radio-Unlicensed (NR-U) study item. On the other hand, artificial intelligence (AI) has attracted enormous attention to implement 5G and beyond systems, which is known as Intelligent Radio (IR). To tackle the challenges of unlicensed spectrum networks in 4G/5G/B5G systems, a lot of works have been done, focusing on using Machine Learning (ML) to support resource allocation in LTE-LAA/NR-U and Wi-Fi coexistence environments. Generally speaking, ML techniques are used in IR based on statistical models established for solving specific optimization problems. In this paper, we aim to conduct a comprehensive survey on the recent research efforts related to unlicensed cellular networks and IR technologies, which work jointly to implement 5G and beyond wireless networks. Furthermore, we introduce a positioning assisted LTE-LAA system based on the difference in received signal strength (DRSS) to allocate resources among UEs. We will also discuss some open issues and challenges for future research on the IR applications in unlicensed cellular networks.

• Journal of Ceramic Processing Research
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• v.20 no.spc1
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• pp.109-112
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• 2019

γ-dicalcium silicate(γ-C2S) is known as a polymorphism of belite. Due to its high CO2 fixed capacity and the low CO2 emission production process, γ-C2S has attracted more and more attention of researchers. For the further development of application of γ-C2S in building construction industry. In this study, we aim to investigate the method for synthesizing high purity of γ-C2S. The influence of different raw materials and calcination temperatures on the purity of γ-C2S was also evaluated. Several Ca bearing materials were selected as the calcium source, the materials which' s main component is SiO2 were used as the silicon source. Raw materials were mixed and were calcined under different temperatures. The results reveal that the highest purity could be obtained using Ca(OH)2 and SiO2 powder as raw materials. And for the practical application, a relatively economic synthesis method using natural mineral materials- limestone and silica sand as raw materials was developed, by this method, the purity of the synthetic γ-C2S was 77.6%.