• Nuclear Engineering and Technology
• /
• v.54 no.7
• /
• pp.2408-2417
• /
• 2022

The nanoindentation behavior of P92 steel with thermomechanical treatment under 3.5 MeV Fe¹³⁺ ion irradiation at room temperature, 400 and 700 ℃ was investigated. Pop-in behavior is observed for all the samples with and without irradiation at room temperature, while the temperature dependence of pop-in behavior is only observed in irradiated samples. The average load and penetration depth at the onset of pop-in increase as the irradiation temperature increases, in line with the results of the maximum shear stress. Irradiation induced hardening is exhibited for all irradiated samples, but there is a significant reduction in the hardness of sample irradiated at 700 ℃ in comparison to the samples irradiated at room temperature and 400 ℃. The ratio of hardness to elastic modulus for all samples decreases with increasing penetration depth except for samples at 700 ℃. With the increasing of irradiation temperature, the ratio of the irreversible work to the total work gradually decreases. In contrast, it increases for samples without irradiation.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.10
• /
• pp.3211-3229
• /
• 2022

To solve the problems existing in the process of Weibo disaster rumor recognition, such as lack of corpus, poor text standardization, difficult to learn semantic information, and simple semantic features of disaster rumor text, this paper takes Sina Weibo as the data source, constructs a dataset for Weibo disaster rumor recognition, and proposes a deep learning model BERT_AT_Stacked LSTM for Weibo disaster rumor recognition. First, add adversarial disturbance to the embedding vector of each word to generate adversarial samples to enhance the features of rumor text, and carry out adversarial training to solve the problem that the text features of disaster rumors are relatively single. Second, the BERT part obtains the word-level semantic information of each Weibo text and generates a hidden vector containing sentence-level feature information. Finally, the hidden complex semantic information of poorly-regulated Weibo texts is learned using a Stacked Long Short-Term Memory (Stacked LSTM) structure. The experimental results show that, compared with other comparative models, the model in this paper has more advantages in recognizing disaster rumors on Weibo, with an F1_Socre of 97.48%, and has been tested on an open general domain dataset, with an F1_Score of 94.59%, indicating that the model has better generalization.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.10
• /
• pp.3419-3437
• /
• 2022

Anonymization technology is an important technology for privacy protection in the process of data release. Usually, before publishing data, the data publisher needs to use anonymization technology to anonymize the original data, and then publish the anonymized data. However, for data publishers who do not have or have less anonymized technical knowledge background, how to configure appropriate parameters for data with different characteristics has become a more difficult problem. In response to this problem, this paper adds a historical configuration scheme resource pool on the basis of the traditional anonymization process, and configuration parameters can be automatically recommended through the historical configuration scheme resource pool. On this basis, a privacy model hybrid recommendation algorithm for user satisfaction is formed. The algorithm includes a forward recommendation process and a reverse recommendation process, which can respectively perform data anonymization processing for users with different anonymization technical knowledge backgrounds. The privacy model hybrid recommendation algorithm for user satisfaction described in this paper is suitable for a wider population, providing a simpler, more efficient and automated solution for data anonymization, reducing data processing time and improving the quality of anonymized data, which enhances data protection capabilities.

• Wind and Structures
• /
• v.32 no.5
• /
• pp.487-499
• /
• 2021

The wind-blown sand effect on the high-speed train is investigated. Unsteady RANS equation and the SST k-ω turbulent model coupled with the discrete phase model (DPM) are utilized to simulate the two-phase of air-sand. Sand impact force is calculated based on the Hertzian impact theory. The different cases, including various wind velocity, train speed, sand particle diameter, were simulated. The train's flow field characteristics and the sand impact force were analyzed. The results show that the sand environment makes the pressure increase under different wind velocity and train speed situations. Sand impact force increases with the increasing train speed and sand particle diameter under the same particle mass flow rate. The train aerodynamic force connected with sand impact force when the train running in the wind-sand environment were compared with the aerodynamic force when the train running in the pure wind environment. The results show that the head car longitudinal force increase with wind speed increasing. When the crosswind speed is larger than 35m/s, the effect of the wind- sand environment on the train increases obviously. The longitudinal force of head car increases 23% and lateral force of tail increases 12% comparing to the pure wind environment. The sand concentration in air is the most important factor which influences the sand impact force on the train.

• Journal of Platform Technology
• /
• v.10 no.3
• /
• pp.11-20
• /
• 2022

South Korea is now recognized as a world leader in the field of digital government thanks to a president who had insight in the field of e-Government more than 20 years ago. Today, many countries around the world are establishing various strategies to cope with the great digital transformation beyond the industrial society and the information society. The Korean government is also establishing and promoting digital government policies to respond to such a global digital transformation. In South Korea, the digital platform government policy began in 2022. Therefore, it is an early stage of policy formation, and many details are not well known yet. Recently, the Korean government announced the vision, three goals, and five strategies for realizing a digital platform government. And specific digital platform government projects that can be implemented are selected. In order to successfully implement a digital platform government, the following three policies should be prioritized. First, the digital platform government should be approached from the perspective of total government innovation, not industry revival. Second, the political perspective should be excluded from ICT policy. Third, the vision and strategy of the digital platform government should be established and clearly presented to the public. And based on this, strong governance should be formed and strongly promoted centered on the leadership of the president.

• Journal of Microbiology and Biotechnology
• /
• v.32 no.12
• /
• pp.1506-1514
• /
• 2022

Allergic contact dermatitis (ACD) is an allergen-specific T-cell-mediated inflammatory response, albeit with unclear pathogenesis. Exosomes are nanoscale extracellular vesicles secreted by several cell types and widely distributed in various biological fluids. Exosomes affect the occurrence and development of ACD through immunoregulation among other ways. Nevertheless, the role of exosomes in ACD warrants further clarification. This review examines the progress of research into exosomes and their involvement in the pathogenesis, diagnosis, and treatment of ACD and provides ideas for exploring new diagnostic and treatment methods for this disease.

• Journal of the Daesoon Academy of Sciences
• /
• v.31
• /
• pp.1-45
• /
• 2018

Daesoon Jinrihoe is one of Korea's most influential religious organizations. Its doctrines and creeds include a rich variety of concepts, and among these, the philosophical notion of 'feminine virtue' holds tremendous value. This paper will explore the multitude meanings of feminine virtue, assume these as a foundation, and then examine the doctrines of Daesoon Jinrihoe to analyze the universality and uniqueness of the philosophical notion of feminine virtue. Additionally, background theoretical points of interest and distinctive features will likewise be analyzed to show the truly valuable lessons that this concept holds for today and why it is so worthy of research and promotion.

• Geomechanics and Engineering
• /
• v.32 no.4
• /
• pp.411-426
• /
• 2023

Soft clay is widely distributed in the southeast coastal areas of China. Many large underground structures, such as subway stations and underground pipe corridors, are shallow buried in the soft clay foundation, so the dynamic characteristics of the soft clay must be considered to the seismic design of underground structures. In this paper, the dynamic characteristics of saturated soft clay in Shanghai under the bidirectional excitation for earthquake loading are studied by dynamic triaxial tests, comparing the backbone curve and hysteretic curve of the saturated soft clay under different confining pressures with those under different vibration frequencies. Considering the coupling effects of the confining pressure and the vibration frequency, a fitting model of the maximum dynamic shear modulus was proposed by the multiple linear regression method. The M-D model was used to fit the variations of the dynamic shear modulus ratio with the shear strain. Based on the Chen model and the Park model, the effects of the consolidation confining pressure and the vibration frequency on the damping ratio were studied. The results can provide a reference to the earthquake prevention and disaster reduction in soft clay area.

• Trans-
• /
• v.16
• /
• pp.33-68
• /
• 2024

In a rapidly growing digital economic environment, NFT has emerged as a hot topic in the art field. However, in China, NFT art is developing slowly due to constraints related to China's political economy and socio-cultural situation. Due to strict management and control, the circulation of cryptocurrency is limited, and the level of public awareness and acceptance of NFT art and market maturity are still low. Despite these limitations, this paper predicts that Chinese art creators and market participants can build an online personal art IP model that suits the characteristics of the Chinese market and explores the current status and possibilities.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.8
• /
• pp.2082-2102
• /
• 2024

Accurate segmentation of magnetic resonance (MR) images is crucial for providing doctors with effective quantitative information for diagnosis. However, the presence of weak boundaries, intensity inhomogeneity, and noise in the images poses challenges for segmentation models to achieve optimal results. While deep learning models can offer relatively accurate results, the scarcity of labeled medical imaging data increases the risk of overfitting. To tackle this issue, this paper proposes a novel fuzzy c-means (FCM) model that integrates a deep learning approach. To address the limited accuracy of traditional FCM models, which employ Euclidean distance as a distance measure, we introduce a measurement function based on the skewed normal distribution. This function enables us to capture more precise information about the distribution of the image. Additionally, we construct a regularization term based on the Kullback-Leibler (KL) divergence of high-confidence deep learning results. This regularization term helps enhance the final segmentation accuracy of the model. Moreover, we incorporate orthogonal basis functions to estimate the bias field and integrate it into the improved FCM method. This integration allows our method to simultaneously segment the image and estimate the bias field. The experimental results on both simulated and real brain MR images demonstrate the robustness of our method, highlighting its superiority over other advanced segmentation algorithms.