Abstract:COVID-19 has led to an unprecedented surge in unemployment associated with increased anxiety, stress, and loneliness impacting the well-being of various groups of people (based on gender and age). Given the increased unemployment rate, this study intends to understand if the different dimensions of well-being change across age and gender. By quantifying sentiment, stress, and loneliness with natural language processing tools and one-way, between-group multivariate analysis of variance (MANOVA) using Reddit dat… Show more
“…Compared to the aforementioned methods, the algorithm proposed in this study demonstrates improved performance in handling complex splicing scenarios like the one shown in <Figure 2>. We will detail this method in the following chapters and validate its effectiveness through a series of experiments [3].…”
With the development and widespread application of digital image processing technology, image splicing has become a common method of image manipulation, raising numerous security and legal issues. This paper introduces a new splicing image detection algorithm based on the statistical characteristics of natural images, aimed at improving the accuracy and efficiency of splicing image detection. By analyzing the limitations of traditional methods, we have developed a detection framework that integrates advanced statistical analysis techniques and machine learning methods. The algorithm has been validated using multiple public datasets, showing high accuracy in detecting spliced edges and locating tampered areas, as well as good robustness. Additionally, we explore the potential applications and challenges faced by the algorithm in real-world scenarios. This research not only provides an effective technological means for the field of image tampering detection but also offers new ideas and methods for future related research.
“…Compared to the aforementioned methods, the algorithm proposed in this study demonstrates improved performance in handling complex splicing scenarios like the one shown in <Figure 2>. We will detail this method in the following chapters and validate its effectiveness through a series of experiments [3].…”
With the development and widespread application of digital image processing technology, image splicing has become a common method of image manipulation, raising numerous security and legal issues. This paper introduces a new splicing image detection algorithm based on the statistical characteristics of natural images, aimed at improving the accuracy and efficiency of splicing image detection. By analyzing the limitations of traditional methods, we have developed a detection framework that integrates advanced statistical analysis techniques and machine learning methods. The algorithm has been validated using multiple public datasets, showing high accuracy in detecting spliced edges and locating tampered areas, as well as good robustness. Additionally, we explore the potential applications and challenges faced by the algorithm in real-world scenarios. This research not only provides an effective technological means for the field of image tampering detection but also offers new ideas and methods for future related research.
“…This underscores the connection between living alone and dietary patterns and body weight. Moreover, Huang et al emphasized the psychological health challenges faced by women during the COVID-19 pandemic, offering insights into the importance of gender in the health context [33]. Finally, Steyn and Mchiza delved into the relationship between obesity and the nutrition transition in sub-Saharan Africa [34].…”
Background
Adults living alone represent a growing population group in China. Understanding the prevalence of body mass index (BMI) categories and their associations with demographic and lifestyle factors among this group is essential for informing targeted interventions and public health policies.
Methods
In this population-based cross-sectional study, we used individual-level data from the 2011–2021 China General Social Survey. Main outcomes were prevalence of BMI categories adjusted for gender and age, using logistic regression and model-predicted marginal prevalence to estimate BMI categories prevalence.
Results
We analyzed 9,077 single-living Chinese adult participants. The primary-adjusted prevalence of BMI categories varied across different genders and age groups. Underweight was more prevalent in females (12.73%; 95% CI: 12.31% - 13.14%) than in males (7.54%; 95% CI: 7.19% - 7.88%), while overweight and obesity were higher in males. Primary-adjusted underweight prevalence was highest among the 18–24 years age group (22.09%; 95% CI: 20.17% - 24.01%) and decreased with age. Primary-adjusted overweight prevalence increased with age, peaking in the 45–54 years age group (41.94%; 95% CI: 40.96% - 42.93%). Primary-adjusted obesity prevalence exhibited a fluctuating pattern across age groups, with the highest prevalence observed in the 45–54 years age group (9.81%; 95% CI: 9.19% - 10.44%).
Conclusion
Our findings reveal significant associations between BMI categories and demographic and lifestyle factors among adults living alone in China. These results can inform targeted interventions and public health policies aimed at promoting healthy weight management and addressing the unique health challenges faced by single-living individuals in China.
“…The biggest difference between edge computing and cloud computing is that cloud computing provides services in the cloud, while edge computing services provide services near the data collection, and the location shifts from the cloud to the edge node or edge server. [6] It can be said that edge computing is an extension of cloud computing, and it is cloud computing that sinks some businesses to the edge layer.…”
Intelligent transportation system is a comprehensive system engineering, involving real-time data processing, security and privacy protection and other challenges. This paper discusses the key role of edge computing in intelligent transportation, especially its combination with SLAM technology. Edge computing enables faster data processing and response times by placing computing and data storage resources near the data source and end users, improving the efficiency and reliability of intelligent transportation systems. At the same time, edge computing can also enhance information security and privacy protection, and bring more possibilities for the future development of intelligent transportation systems. In the future, with the progress and development of technology, we can look forward to the deeper application of edge computing and SLAM technology in the field of intelligent transportation, bringing more innovation and development to smart city transportation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.