• Earthquakes and Structures
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• 제23권6호
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• pp.527-534
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• 2022

EDCC (Eco-Friendly Ductile Cementitious Composites) is a recently created class of engineered cementitious composites that exhibit extremely high ductility and elastoplastic behavior under pure tension. EDCC contains reduced amounts of cement and very large volumes of fly ash. Due to these properties, EDCC has become one of the solutions to use in seismic upgrading. This paper discloses previous studies and research that discussed the seismic upgrading of unreinforced, non-grouted, unconfined, and non-load bearing masonry walls which are called URM infill walls using the EDCC technique. URM infill wall is one of the weak links in the building structure to withstand the earthquake waves, as the brittle behavior of the URM infill walls behaves poorly during seismic events. The purpose of this study is to fill a knowledge gap about the theoretical and experimental ways to use the EDCC in URM infill walls. The findings reflect the ability of the EDCC to change the behavior from brittle to ductile to a certain percentage behavior, increasing the overall drift before collapse as it increases the energy dissipation, and resists significant shaking under extensive levels with various types and intensities.

• Structural Engineering and Mechanics
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• 제82권3호
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• pp.313-323
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• 2022

Steel laminated elastomeric bearings are commonly used in bridge structures to control displacements and rotations and transfer forces from the superstructure to the substructure. Proper knowledge of design, fabrication and erection procedures is important to ensure stability and adequate structural performance during the lifetime of the bridge. Difference in elevations sometimes leads to large size gaps between the bearing and the girder which makes the grout thickness that is commonly used for leveling deviate beyond standards. This paper investigates the structural response of High Strength Fiber Reinforced Cementitious (HSFRC) thin plinths that are used to close gaps between bearing pads and precast girders. An experimental program was developed for this purpose where HSFRC plinths of different size were cast and tested under vertical loads that simulate bridge loading in service. The structural performance of the plinths was closely monitored during testing, mainly crack propagation, vertical reaction and displacement. Analytically, the HSFRC plinth was analyzed using the beam on elastic foundation theory as the supporting elastomeric bearing pads are highly compressible. Closed form solutions were derived for induced displacement and forces and comparisons were made between analytical and experimental results. Finally, recommendations were made to facilitate the practical use of HSFRC plinths in bridge construction based on its enhanced load carrying capacity in shear and flexure.

• Molecules and Cells
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• 제46권1호
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• pp.41-47
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• 2023

The rapid development of mRNA vaccines has contributed to the management of the current coronavirus disease 2019 (COVID-19) pandemic, suggesting that this technology may be used to manage future outbreaks of infectious diseases. Because the antigens targeted by mRNA vaccines can be easily altered by simply changing the sequence present in the coding region of mRNA structures, it is more appropriate to develop vaccines, especially during rapidly developing outbreaks of infectious diseases. In addition to allowing rapid development, mRNA vaccines have great potential in inducing successful antigen-specific immunity by expressing target antigens in cells and simultaneously triggering immune responses. Indeed, the two COVID-19 mRNA vaccines approved by the U.S. Food and Drug Administration have shown significant efficacy in preventing infections. The ability of mRNAs to produce target proteins that are defective in specific diseases has enabled the development of options to treat intractable diseases. Clinical applications of mRNA vaccines/therapeutics require strategies to safely deliver the RNA molecules into targeted cells. The present review summarizes current knowledge about mRNA vaccines/ therapeutics, their clinical applications, and their delivery strategies.

• Journal of Platform Technology
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• 제11권1호
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• pp.72-84
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• 2023

With the rise of the Internet of Things, the security of such lightweight computing environments has become a hot topic. Lightweight block ciphers that can provide efficient performance and security by having a relatively simpler structure and smaller key and block sizes are drawing attention. Due to these characteristics, they can become a target for new attack techniques. One of the new cryptanalytic attacks that have been attracting interest is Neural cryptanalysis, which is a cryptanalytic technique based on neural networks. It showed interesting results with better results than the conventional cryptanalysis method without a great amount of time and cryptographic knowledge. The first work that showed good results was carried out by Aron Gohr in CRYPTO'19, the attack was conducted on the lightweight block cipher SPECK-/32/64 and showed better results than conventional differential cryptanalysis. In this paper, we first apply the Differential Neural Distinguisher proposed by Aron Gohr to the block ciphers HIGHT and GOST to test the applicability of the attack to ciphers with different structures. The performance of the Differential Neural Distinguisher is then analyzed by replacing the neural network attack model with five different models (Multi-Layer Perceptron, AlexNet, ResNext, SE-ResNet, SE-ResNext). We then propose a Related-key Neural Distinguisher and apply it to the SPECK-/32/64, HIGHT, and GOST block ciphers. The proposed Related-key Neural Distinguisher was constructed using the relationship between keys, and this made it possible to distinguish more rounds than the differential distinguisher.

• Applied Microscopy
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• 제50권
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• pp.23.1-23.9
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• 2020

We propose an effective deep learning model to denoise scanning transmission electron microscopy (STEM) image series, named Noise2Atom, to map images from a source domain 𝓢 to a target domain 𝓒, where 𝓢 is for our noisy experimental dataset, and 𝓒 is for the desired clear atomic images. Noise2Atom uses two external networks to apply additional constraints from the domain knowledge. This model requires no signal prior, no noise model estimation, and no paired training images. The only assumption is that the inputs are acquired with identical experimental configurations. To evaluate the restoration performance of our model, as it is impossible to obtain ground truth for our experimental dataset, we propose consecutive structural similarity (CSS) for image quality assessment, based on the fact that the structures remain much the same as the previous frame(s) within small scan intervals. We demonstrate the superiority of our model by providing evaluation in terms of CSS and visual quality on different experimental datasets.

• Smart Structures and Systems
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• 제29권5호
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• pp.677-691
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• 2022

Water cycle algorithm (WCA) has been a very effective optimization technique for complex engineering problems. This study employs the WCA for simultaneous prediction of heating load (L_H) and cooling load (L_C) in residential buildings. This algorithm is responsible for optimally tuning a neural network (NN). Utilizing 614 records, the behavior of the L_H and L_C is explored and the captured knowledge is then used to predict for 154 unanalyzed building conditions. Since the WCA is a population-based algorithm, different numbers of the searching agents were tested to find the most optimum configuration. It was observed that the best solution is discovered by 500 agents. A comparison with five newly-developed benchmark optimizers, namely equilibrium optimizer (EO), multi-tracker optimization algorithm (MTOA), slime mould algorithm (SMA), multi-verse optimizer (MVO), and electromagnetic field optimization (EFO) revealed that the WCANN predicts the desired parameters with considerably larger accuracy. Obtained root mean square errors (1.4866, 2.1296, 2.8279, 2.5727, 2.5337, and 2.3029 for the L_H and 2.1767, 2.6459, 3.1821, 2.9732, 2.9616, and 2.6890 for the L_C) indicated that the most reliable prediction was presented by the proposed model. The EFONN, however, provided a more time-effective solution. Lastly, an explicit predictive formula was elicited from the WCANN.

• Wind and Structures
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• 제36권3호
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• pp.215-220
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• 2023

We study the progressive full-scale wind tunnel tests on a high solidity vertical axis wind turbine (VAWT) for various tip speeds and pitch angles to understand the VAWT shaft system's dynamics using 0-1 Test for chaos. We identify that while varying rotor speed (tip speed) of the turbine, the system's dynamics change from periodic to chaotic through quasiperiodic and strange non-chaotic (SNA) states. The present study is the first experimental evidence for the existence of these states in the VAWT shaft system to the best of our knowledge. Using the asymptotic growth value Kc in 0-1 test, when the turbine operates at the low tip speeds and high pitch angles for low incoming wind speeds, the system behaves periodic (Kc ≈ 0). However, when the incoming wind speed increases further the system's dynamics shift from periodic to chaotic vibrations through quasi-periodic and SNA. This phenomenon is due to the dynamic stalling of blades which induces chaotic vibration in the VAWT shaft system. Further, the singular continuous spectrum method validates the presence of SNA and differentiates the SNA from chaotic vibrations.

• Earthquakes and Structures
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• 제25권5호
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• pp.325-342
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• 2023

The damping modification factor (DMF) is used to modify the 5%-damped response spectrum to produce spectral values that correspond to other necessary damping ratios for seismic design. The DMF has been the subject of numerous studies, and it has been discovered that seismological parameters like magnitude and distance can have an impact on it. However, DMF formulations incorporating these seismological parameters cannot be directly applied to seismic design because these parameters are not specified in the present seismic codes. The goal of this study is to develop a formulation for the DMF that can be directly applied in seismic design and that takes the effects of magnitude, distance, and site conditions into account. To achieve this goal, 16660 ground motions with magnitudes ranging from 4 to 9 and epicentral distances ranging from 10 to 200 km are used to systematically study the effects of magnitude, distance, and site conditions on the DMF. Furthermore, according to the knowledge that magnitude and distance affect the DMF primarily by changing the spectral shape, a spectral shape factor is adopted to reflect influences of magnitude and distance, and a new formulation for the DMF incorporating the spectral shape factor is developed. In comparison to the current formulations, the proposed formulation provides a more accurate prediction of the DMF and can be employed directly in seismic design.

• International Journal of Internet, Broadcasting and Communication
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• 제15권4호
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• pp.199-204
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• 2023

Periodic assessment of reservoir capacity is essential for better water resources management and planning for the future water use. Reservoirs and water storage structures raised on the rivers are subjected to sedimentation and he sedimentation is caused by deposition of eroded sediment particles carried by the streams. Knowledge of reservoir sedimentation is important to estimate avaliable storage capacity for optimum reservoir operation and scheduling water release. In recent years, remote sensing and GIS techniques have emerged as an important tool in carrying out reservoir capacity analysis and water management. The reduction in storage capacity as compared to the original capacity at the time of reservoir impounding is indicative of sediment deposition. In this study, the application of GIS and remote sensing techniques were applied to assess the sediment deposition, losses in the reservoir storage and the revised cumulative capacity. Satellite images covering Pyodongdong reservoir were analyzed using Erdas Imagine and ArcGIS softwares.Cumulative capacities at different levels were also calculated and we estimated that the revised live storage was 84.2Mft3 in 2021 and 64.3Mft3 in 2022 while the original capacity was 22.8 and 53.6Mft3 in 2021 and 2022.

• 한국건설관리학회논문집
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• 제25권3호
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• pp.68-82
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• 2024

The planning stage of laser scanning is crucial for acquiring high-quality 3D source data. It involves assessing the target space's environment and formulating an effective measurement strategy. However, existing practices often overlook on-site conditions, with decisions on scanner deployment and scanning locations relying heavily on the operators' experience. This approach has resulted in frequent modifications to scanning locations and diminished 3D data quality. Previous research has explored the selection of optimal scanner locations and conducted preliminary reviews through simulation, but these methods have significant drawbacks. They fail to consider scanner inaccuracies, do not support the use of multiple scanners, rely on less accurate 2D drawings, and require specialized knowledge in 3D modeling and programming. This study introduces an optimization technique for laser scanning planning using 3D simulation to address these issues. By evaluating the accuracy of scan data from various laser scanners and their positioning for scanning a retaining wall structure in a small-scale building, this method aids in refining the laser scanning plan. It enhances the decision-making process for end-users by ensuring data quality and reducing the need for plan adjustments during the planning phase.