bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on the RS-based landscape patterns of tourist cities using Guilin as an illustration
Authors: Cao Wanzheng , Chen Jianguo , Guo Song
Published: April 2023

In China and beyond, Guilin is a well-known tourism destination. The city is home to numerous tourist attractions. By 2021, the area of forest land in the study area would account for the biggest proportion, according to the analysis of remote sensing data. The area of water and cultivated land shrank in comparison to 2000, and although the area of construction land expanded year over year, it indicated a decreasing tendency. The driving force analysis reveals that the protection and maintenance of landscape resources must be the primary focus of urban development if a sustainable tourism city is to be created. The study region's center urban area is primarily intended to safeguard natural resources and promote tourism, so the rate of expansion of the area used for building is declining. Guilin proposed the idea of creating two city centers, which successfully overcame the conflict between urban growth and environmental conservation, enhanced the study region's ecological conditions, and expanded the area of forested land. It is suggested to adhere to the policy of the development of the two urban centers by evaluating the historical development of Guilin City. The spatial interaction between various land uses should be fairly arranged with the aim of creating a landscaped city as part of the future development of Lingui New Area. Maximize the landscape resources of the center urban area, restrict the growth of the construction area in the central urban area, carry out micro-transformation on idle land in the city, create pocket parks and green spaces, and build rural tourism on agricultural land at the outskirts of the city.
Analysis of short video and city image communication in the new media environment
Authors: Zhang Mengjie
Published: April 2023

City image is the social impression of the city, which affects the public's evaluation of the city. With the development of new media technology, city image communication has separated from the previous way of official media and entered the stage of mobile terminal short video, and improved the sense of acceptance of publicity with the help of network video. With the help of short videos, cities can shape their urban image, build urban recognition, and attract public attention. This paper focuses on the analysis of the fragmentation of the city image in the short video communication, matching the characteristics of the city and creating the network meme characteristics. And when facing the dilemma of homogenization and mimicry in communication, cities adopt conventional methods in four aspects: communication subject, communication content, communication perspective, and distribution.
A study on the intervention of film therapy in the field of judicial social work
Authors: Yin Wanping
Published: April 2023

Judicial social work is an important force in promoting the construction of a socialist society under the rule of law with Chinese characteristics, and in the face of the current complex social situation, it is necessary to introduce new working methods to better fulfil the objectives of early prevention, timely intervention, behavioural modification and empowerment. The effectiveness of film therapy in the psychological treatment and personal growth of clients has been recognised in other fields of social work, but its intervention in judicial social work is somewhat lacking, and it is worth further exploring the feasibility of combining the two.
Reflecting the Study of Foreign Language Learning Motivation in China from 2012 to 2021
Authors: Ding Yu
Published: April 2023

This paper reviews the articles on foreign language learning motivation published in the core journals of Peking University and on CSSCI in the past decade from 2012 to 2021. The articles are collected from 31 journals, mainly from the theoretical research and empirical research on foreign language learning motivation in China, and from the development trend, research content, research object The research methods and tools are statistically analyzed. The results show that the number of studies on foreign language learning motivation in China has generally declined in recent years. Also, the number of empirical research is generally more than that of theoretical research. Then. the number of articles about the relationship between motivation and learning effectiveness is the largest in the research content. The overwhelming majority of the literatures studied by questionnaire alone or jointly; Among the research objects, undergraduates are the major groups that being researched as participants. Finally, this paper reviews the current situation of foreign language learning motivation research in China.
Research on the Coordinated Economic Development of Beijing-Tianjin-Hebei Urban Agglomeration Based on the Measurement of Compactness
Authors: Xue Bowen
Published: April 2023

Urban agglomeration is an important growth pole for China's future economic development. In recent years, the national high level has paid more and more attention to supporting the development of various urban agglomerations in China. As the third-largest urban agglomeration in China, the Beijing-Tianjin-Hebei urban agglomeration is led by Beijing and Tianjin and develops together with 11 prefecture-level cities in Hebei Province. However, the gap between the top two Yangtze River Delta and Pearl River Delta urban agglomerations is still not small. Meanwhile, the gap between different cities within the Beijing-Tianjin-Hebei urban agglomeration has always been considerable, and the coordinated development of each city is less effective than that of the other two urban agglomerations. This paper first calculates the compactness index to obtain the changes in the compactness of the Beijing-Tianjin-Hebei region from 2013 to 2019 and analyzes the development trend of the region in recent years. Among them, the compactness of space is growing rapidly, and the growth rate of industrial compactness and traffic compactness is relatively slow. It is based on identifying the core area of the urban agglomeration based on population density. We put forward ideas on achieving better coordinated regional developments and accelerating integrations.
How Risk Perception Impacts Cervical Cancer Knowledge Acquisition in China: From an Adapted Cognitive Mediation Model Perspective
Authors: Yang Chenxi , You Jianing , Zhang Yunya
Published: April 2023

As a result of the relatively late implementation of HPV vaccination in China, many young Chinese women have weak awareness and limited knowledge about cervical cancer. This study developed an adapted cognitive mediation model with risk perception as a key factor that prompts serial mediation effects and ultimately influences cervical cancer knowledge acquisition. An online survey was conducted among 1066 Chinese women aged 15-35. The results were analyzed for three age groups, which mostly supported the hypothesized model. Risk perception was positively correlated with elaboration and cervical cancer knowledge acquisition, but only with attention to cervical cancer-related information among participants aged 20-35. Attention to cervical cancer-related information was positively associated with elaboration while having no significant correlation with knowledge acquisition. Elaboration was positively associated with knowledge acquisition. Indirect effects between risk perception and knowledge acquisition through elaboration were found. The impact of risk perception on knowledge acquisition was also sequentially mediated by attention and elaboration among participants aged 28-35. The results indicate a general tendency that an individual’s level of risk perception, attention to cervical cancer-related information, elaborative processing of information, and the amount of knowledge gained increase with age. Adolescents aged 15-19 particularly lack risk perception and attention to health information. The implications of the results are discussed in detail based on previous studies. Research limitations and future directions are also suggested.
A Comparison Between the Feminism of Scarlett and Melanie
Authors: Han Ruoqi
Published: April 2023

Widely considered as a classic feminist work, there are many studies of Gone With the Wind from the perspective of feminism in academia. Most of these studies focus on the feminist spirit of its protagonist Scarlett, while the feminism of another important female character Melanie has always been ignored and even considered as the representation of women who completely accept the repression of patriarchy. Based on the text analysis, this research makes a contrastive analysis of Scarlett and Melanie, analyzes the similarities and differences between them and taps into their feminist spirits from the perspective of feminist literary criticism. By comparing these two female characters, the research finds the two main differences lie in their handling of interpersonal relationships and responses toward patriarchal rules are obvious—— from the perspective of interpersonal relationships, the egoism of Scarlett contrasts with Melanie’s altruism; in the face of the patriarchal rules, Melanie’s female subjectivity and independence are not as noticeable as those of Scarlett. Although the differences between them are obvious, they still share similarities in their subversion towards the patriarchy and their occupation of a position more central than the male characters in Gone with the Wind. This research on these two female characters has implications for further studies of female character creation and feminist literary criticism, as well as the distinctive feminism of Mary Mitchell, reflected in her portrayal of these two female characters.
Analysis of the Similar Characteristics in the Works of Dickinson and Bishop
Authors: Zhang Yiming
Published: April 2023

Emily Dickinson and Elizabeth Bishop are both the most influential poets in western literary history. They both lived in a time of great change, and they both were seen as more silent than men. Dickinson lived a reclusive life until her death, she devoted almost her whole life to writing, and created 1775 poems in her lifetime. Her lonely life nourished her poetry, and despite frequent illness and unrequited affection, Dickinson’s relationship with poetry was inextricably inseparable. As for the modern American poet Bishop, she always shuttles between different countries in her life. This experience of displacement and migration is not only her pleasure, but also the source of her loneliness and pain. There are many similarities in the life and creation of Bishop and Dickinson, both of whom have experienced the misfortune of growing up, and both have doubts about the identity as poets and as women. This paper explores the similarities between the two poets’ creations and the causes from the aspects of time, physical condition and spiritual pursuit. The causes are their thoughts of life, death and female identity, as well as their pursuit of peace, which takes modern American poetry to a whole new level.
An Analytical Study of Family Investment in Education at the Pre-school Level in China - A Comparative Analysis Based on Eastern, Central and Western China
Authors: Cheng Ziyang , Yu Jiayuan , Yuan Haining
Published: April 2023

Since the publication of China's National Medium- and Long-Term Education Reform and Development Plan in 2010 and the active development of preschool education, the development of preschool education has gradually received attention from all sectors and the positive effects of the expansion of preschool education in China are evident. However, as the national household share of preschool education still falls short of international standards, the issue of education consumption by households affected by their individual economic development in the expansion of preschool education cannot be ignored. This paper examines the relationship between factors such as household socio-economic income and cultural background and education expenditure of preschool children's families, based on a regression analysis of macro data from the provincial statistical bureaus of the three provinces and micro data from the China Household Tracking Survey in 2018, from the perspective of combining macro and micro data in Guangdong, Henan and Gansu provinces selected in the eastern, central and western regions of China respectively. The study found that for the families themselves, the higher the economic level, the higher the expenditure on preschool education. Also, the higher the level of education of the mother, the higher the expenditure on preschool education. For different regions, the more economically developed the region, the more parents are willing to spend more on their children's pre-school education.
How Family Environment Influence the Social Role of Female Adolescents
Authors: Ji Xin
Published: April 2023

This research discusses the influence of family environment on the social role of female adolescents. Family expectations, educational expectations and occupational expectations have been considered crucial elements for shaping the perspective and social role of adolescents. In this study, it has been found that female adolescents are often expected to focus on roles such as caring and house holdings while males are expected to be the primary breadwinners. These expectations are based on societal gender roles and stereotypes, as well as cultural, social, and economic factors. Differentiated parental expectations can have both positive and negative effects on adolescent development, such as providing clarity and structure but also reducing self-esteem and reinforcing harmful gender biases. This research also discusses the impact of stereotypical educational expectations on adolescent development, with female adolescents often being expected to take subjects such as psychology and biology while males are more likely to take subjects including mathematics and physics. Lastly, this study highlights that a lack of employment opportunities in certain fields and discrimination can limit the career opportunities available to female adolescents. Some suggestions about parental workshops, community promotion for the welfare of adolescents and rule and policy developments have also been portrayed in this research. These suggestions are considered to be effective strategies for enhancing the positive aspects of societal roles of female adolescents and also help to reduce negative aspects of gender-based discrimination.
How Gender Stereotypes Impact the Career Choice of High School Students
Authors: Kong Linran , Wang Jiayi , Zhang Xinyan
Published: April 2023

Nowadays, gender stereotypes are a common belief or prejudice for both males and females. Negative or positive gender stereotypes may coexist:  women are typically defined as vulnerable, whereas gender stereotypes of men are mostly positive, such as men being more dynamic and logical. Previous research has evidenced that gender stereotypes are perceived differently by the sexes. However, how diverse gender stereotypes can influence adolescents' choices requires comprehensive investigation. This study focuses on the influence of gender stereotypes on adolescents' occupational choices. The study found that most adolescents are influenced by gender stereotypes in their career choices, either from family upbringing or from school upbringing. However, there is a small percentage of adolescents who are firm in their career choice from the beginning to the end and are not influenced by gender stereotypes. To reduce the negative impact of gender stereotypes on adolescents' occupational choices, this experimental study also suggests several strategies, including schools offering courses to properly guide adolescents' gender perceptions.
The Collapse of the Han Empire on the Impact of Daoism
Authors: Xu Minzhe
Published: April 2023

Daoist School has exerted a great influence on shaping Chinese history. However, Daoism did not really appear in China until more than 600 years after the birth of the Daoist School. The special cultural and political shaping of the Eastern Han dynasty led to the transformation of Daoism from a pure idea to a more practical theory. The Han Empire had an elaborate and massive bureaucratic system that ensured that imperial power was concentrated in the hands of the emperor and his trusted ministers. At the end of the Eastern Han dynasty, the government could not maintain a costly bureaucratic system due to the plague, famine, and financial crises. Daoism gained unprecedented freedom to preach. This paper analyzes the late Han dynasty’s unique social and political background through historical materials. Comparing the attitudes of different Daoist tribes towards the government concludes that the true foothold of Daoism in China must be an alliance with aristocrats. At the same time, Daoism has assumed the corresponding social responsibility and gained more people’s trust. However, when Daoist power grew to a certain size, it inevitably attracted the attention of the empire. Different sects have chosen different paths to develop. The Taiping Dao underestimated the empire’s military power, which soon led to its own destruction. The Heavenly Master avoided direct conflict with the empire and achieved their religious and political goals by uniting with local forces when the empire was on its way to destruction.
The Greek Root of Byzantine Emperor: Constantine the Great, His Images and the Imperial Cult
Authors: Xu Ao
Published: April 2023

In the time of Constantine the Great, the emperor consciously controlled his image to strengthen his presence within the empire to consolidate the imperial power and his rule. In the process, various visual art forms were utilised, with the emperor represented in the form of sculptures, mosaics/paintings, and coin emblems. The use of emperor portraits throughout the secular and sacred spaces reflects Constantine's important role in politics and religion. Constantine showed the element of "worship" in his images. He completed a "self-deification" with subjective initiative, which had important significance in Constantine's time and the political life after his age. In this process, images and ruler cult are two elements that cannot be ignored. In the Byzantine-centered discussion, both features can be traced back to ancient Greece. This paper will show that Constantine used his own image, with images as a tool, along with other means to promote his worship and successfully spread the perception of the concentration of imperial power to the whole society. The use of images and the ruler cult, in turn, is a profound reflection of the Greek roots of the early Byzantine Empire.
Intelligent Diagnosis of Alzheimer's disease
Authors: Huang Ruifan , Xu Huifei
Published: April 2023

In this paper, we combine the knowledge of decision tree model and K-means clustering algorithm with knowledge of statistics to solve the problems of Diagnosis of Alzheimer's disease using brain structure. In the step of selecting features, this paper considers both data-based and theoretical perspectives for the analysis of variance in Alzheimer's disease. Based on the data perspective, the value of variance represents the magnitude of data volatility, i.e., data with data volatility has more abilities to cause data changes in feature classification. Therefore, in this paper, a total of 28 indicators of Site-faq were selected as necessary indicators and histograms were made to observe the volatility. After the above data processing, we Use the attached structural brain features and cognitive behavioral features to design an intelligent diagnosis of Alzheimer's disease. For multi-classification models, this paper uses the K-means algorithm to cluster and continue to cluster MCI into SMC, EMCI, LMCI to observe the difference between cluster centers. After clustering 53 indicators, this paper analyzes the three types of cluster centers, mainly to analyze the different points in the number of clusters, and analyzes the difference in the mean value of the characteristics of the cluster centers, and at the same time, this paper observes the differences between the characteristics by visualizing the data. In the end, we analyze them in relation to the time points to uncover patterns in the evolution of different categories of diseases over time. At the same time, due to the large amount of data, this paper only selects a small sample of five features for analysis.
Research on sentiment analysis methods for text-oriented data
Authors: Deng Yuanfei
Published: April 2023

With the rapid development of information technology, the results obtained from sentiment analysis on a large number of speech information on these platforms can be used for comment classification, product analysis and recommendation, consumption forecast and other aspects of the network platform With the rapid development of information technology, the results obtained from sentiment analysis on a large number of speech information on these platforms can be used for comment classification, product analysis and recommendation, consumption forecast and other aspects of the network platform Sentiment analysis is a practical technique which has become one of the most active research fields in natural language processing. The traditional text sentiment analysis method consumes a lot of human resources, but the coverage of artificial extracted features is the traditional text sentiment analysis method consumes a lot of human resources, but the coverage of artificial extracted features is limited and the artificial irrational behavior will affect the correctness of the results, so the traditional method is not universal. With the development of deep learning, text pre-training language model and knowledge graph technology continue to develop. Aiming at the research of sentiment analysis methods for text data, we summarize the research background and domestic and foreign research status of sentiment analysis methods for text data, and explore the hot research content, key problems, commonly used experimental methods and technical lines of sentiment analysis methods for text text data.
Vehicle target detection algorithm based on yolov5
Authors: He Xing
Published: April 2023

With the rapid advancement of automobile manufacturing technology and the intensification of competition among automobile brands, the development of autonomous driving has been pushed to the forefront of automobile development, which causes approximately $650 billion in losses due to traffic accidents worldwide every year. For in the complex vehicle target scene, because of its many vehicle targets, dense targets often exist between the occlusion, overlap, a variety of different weather reasons, rain, fog, sunny days, etc. resulting in obstruction of the field of view, and the vehicle camera often intercepted images mostly exist blurred, ghosting and other problems, making the vehicle target detection for detailed feature extraction requirements are high, the detection accuracy is often difficult to meet the requirements, proposed based on YOLOv5s vehicle target detection algorithm is proposed. ACmix attention mechanism is introduced to make the model achieve the purpose of expanding the target perception field, adaptively focusing on different target regions, and capturing more information features, etc. The test shows that the accuracy of the model increases by 1.1% on a subset of BDD100K data set after improvement. The accuracy of the improved model increased by 1.1% on the subset of BDD100K dataset and by 1.2% on the PASCAL VOC2007 general dataset.
Research on Water Garbage Detection Algorithm Based on GFL Network
Authors: Yi Nengmin , Luo Weilin
Published: April 2023

Aiming at the problem that existing water surface garbage detection algorithms cannot meet the tradeoff between real-time and accuracy in natural scenes, we propose a GFL (Generalized Focal Loss) based GFL_ HAM algorithm to improve the accuracy of water surface garbage detection, and better apply to water surface garbage detection application scenarios. We have added the HAM (Hybrid Attention Model) module to the feature extraction module (resnet50) of the GFL network to improve the feature extraction capability of the backbone network and the network representation capability. And use the self-constructed garbage detection datasets under natural scenes for training and testing. After analyzing the training process and test results, our network has higher reliability compared to the current mainstream single stage network. Our network can achieve 60.12% mAP on the water surface garbage detection datasets, which is 1.09%, 1.36%, and 1.61% higher than YOLOv3, SSD, and GFL, respectively.
Design and Implementation of Convolutional Neural Network Accelerator Based on FPGA
Authors: Cheng Jixun
Published: April 2023

Convolutional neural network, as a kind of feed-forward neural network, has been widely used in image recognition, speech processing and other fields in recent years. In this paper, an FPGA-based CNN gas pedal is designed to solve the problem of slow running and high-power consumption of CNN on resource-constrained hardware. The design invokes multi-stage pipeline parallel processing technology to accelerate convolutional operations; quantifies network parameters from 32-bit floating-point to 8-bit fixed-point while guaranteeing CNN accuracy, and uses data multiplexing to reduce resource consumption. Experimental results show that the design is 10 times faster than the intel i7-8700 and consumes only 1% of the power of the RTX 2060 at 50MHz.
Detection of floating objects in river based on improved HRNet
Authors: Li Qingtai
Published: April 2023

Human activities and other factors lead to a variety of floating objects in rivers, which seriously affect the quality of human life and natural ecological environment. It has become a widely concerned problem for residents and needs to be solved urgently. Relying on manual inspection to find floating objects is extremely low efficiency, urgent need of intelligent technology to detect and warn in time. To solve the problem of river floating object detection, we proposed an improved HRNet method for river floating object detection. Trunk network HRNet was used to replace the original AlexNet trunk network of Faster-RCNN to detect river floating object, which enhanced the feature extraction ability. A backbone combining DenseNet and HRNet is proposed to optimize the ability to extract details and improve the detection accuracy.
A Review of Video Action Detection Based on Deep Learning
Authors: Zeng Zhuofan
Published: April 2023

Currently, the application of deep learning to solving problems associated with traditional surveillance video analysis has become one of the research hot topics. The video action detection is referred to as detecting the temporal segments containing the action in the video as temporal action proposals. The existing work is mainly classified into two categories: one is to use the low-level details of video to generate action proposals; the other is to use the high-level semantics of video to generate action proposals. By deeply researching the video action detection methods based on deep learning, this paper is an attempt to find out problems with the existing methods and put forward some suggestion for improvement.
A modified YOLOv5 helmet detection algorithm based on Swin Transformer
Authors: Liu Zhongling , Luo Yi , Liu Chanyi
Published: April 2023

For the current stage of helmet detection in complex environments with low accuracy, missed detection and not easy to manage wearing, this paper proposes a YOLOv5 face helmet detection algorithm based on Swin Transformer improvement from the overall semantics of the image. In this paper, experiments are conducted using a self-built dataset to further enhance the performance of the model and improve the accuracy of face helmet detection through Mosaic data enhancement, label smoothing processing, adaptive weighted features combined with Wconcat module and the application of C3TR and C3STR modules to fuse multi-scale information, enhance the feature extraction capability of the network, and improve the generalization and robustness of the model with a self-built dataset . Experiments show that the improved YOLOv5 face helmet detection algorithm mAP based on Swin Transformer improves 5.7% compared with Faster RCNN, 6.1% compared with YOLOV3, 5.3% compared with YOLOV4, and 1.6% compared with the original algorithm. It performs well in helmet face detection tasks in complex environments, achieving real-time detection and higher accuracy, while reducing missed detections.
Kerberos authentication protocol implementation based on DHR atypical construct
Authors: Zhang Tingan
Published: April 2023

As a commonly used identity authentication protocol, the Kerberos authentication protocol uses a symmetric password system, which has significant efficiency advantages but also brings risks such as password guessing and replay attacks. Some existing research combines public key cryptography with Kerberos to greatly enhance its security, but the large amount of computation required for public-private key cryptography leads to lower efficiency. This paper proposes a solution that uses the DHR non-typical construction to provide dynamism and randomness to the Kerberos authentication protocol to improve its security while minimizing efficiency losses. Experimental results show that the improved protocol can resist attacks while ensuring efficiency.
Improving NLP Accuracy with Stack-Propagation and Knowledge Distillation: A Joint Model for Intent Detection and Slot Filling
Authors: Wang Yuan , Yang Zhoumeng , Zhang Xiyan
Published: April 2023

Intent detection and slot filling are fundamental tasks in Natural Language Understanding (NLU), constituting important components of intelligent question-answering systems. These tasks are closely interrelated, forming a core aspect of semantic understanding in natural language processing. In this paper, we propose an architecture using Stack-Propagation to improve the accuracy of NLU tasks. In stack propagation, we use a joint model that mainly incorporates token-level intent detection data with sentence word vectors as input for slot filling to capture intent semantic knowledge. Additionally, we use knowledge distillation (KD) to improve model efficiency and enhance the correlation between the two tasks. Our proposed framework significantly differs from existing joint models as it directly leverages intent information in the joint model and adopts token-level intent information for slot filling to ease error propagation. Furthermore, our model can explicitly incorporate intent information for slot filling with Stack-Propagation, making the interaction procedure more interpretable, while other models only interact with hidden states implicitly between the two tasks. We experimentally evaluated our model on two publicly available datasets, and the results demonstrate that it achieves state-of-the-art performance and outperforms previous methods by a significant margin, indicating its superiority in addressing the slot-filling and intent detection tasks. In future research, we will combine the stack-propagation frame with the KD module in the Transform model, which can boost our model performance to move forward a single step in the NLU task.
Divide-and-Conquer Template Attack on Scloud
Authors: Zhou Yang
Published: April 2023

Since shor proposed the quantum algorithm, the traditional public key cryptosystem is facing the risk of being breached. To address this issue, Post-Quantum Cryptography (PQC), also known as Anti-Quantum Cryptography, has been developed. Among the various PQC techniques, lattice-based cryptography has emerged as a significant area of research due to its many advantages. This paper studies the leakage of post quantum cryptography cloud on physical devices. Discovered that the matrix calculation operation of the Scloud algorithm has an impact on key security. Based on the characteristics of the curve, we propose a divide and conquer template attack method and introduce convolutional neural network technology for template construction. On the Cortex-M3 board, we have demonstrated that the proposed attack can effectively recover the key.
Procedural Modeling Method of Pipe Network Based on Spline Grammar
Authors: Wang Xiaolong
Published: April 2023

The shape grammar is usually used to describe the three-dimensional model with certain regularity, but in the process of constructing the three-dimensional model of industrial pipeline network or urban underground pipeline network, due to the complex wiring characteristics of the pipeline, the pipeline with different changing trajectories is often unable to be described by fixed shape. Therefore, the construction process for 3D pipe networks often requires art developers to spend a lot of time and effort to develop models. Arbitrarily shaped pipes can be effectively described in procedural modeling construction processes by incorporating splines that are inherently variable in nature and combining them as terminator shapes into shape grammar. Based on this theory, this paper proposes that the procedural modeling method based on spline grammar can efficiently complete the procedural construction of pipeline networks, and this method can quickly complete the splicing of pipeline networks. Experimental results show that our method is suitable for pipe network construction projects in different fields.
Research on Video Synopsis Based on Deep Learning Target Detection and Target Trajectory Optimization
Authors: Liu Yue , Luo Li , Hong Weibin
Published: April 2023

In this era of rapid economic and technological development, monitoring is essential for security issues. However, it is also accompanied by the low efficiency of managing and viewing a large number of surveillance videos every day. Traditional methods are gradually unable to meet the requirements of application, and the video field requires algorithm technology that can better solve practical problems. Intelligent monitoring technology is gradually emerging and developing, based on theories such as computer vision, which can solve many monitoring video problems and greatly improve the efficiency of monitoring video work. Through in-depth exploration of existing video synopsis technology algorithms, this article proposes a new video synopsis method that can effectively detect and track videos, thereby greatly improving the efficiency of storage, transmission, and use of surveillance videos. Experiments have shown that this method can effectively concentrate surveillance videos, and compared with existing methods, it has a better synopsis ratio while ensuring the integrity of video information, effectively reducing collisions between targets, effectively reducing overlap between targets, and achieving good visual effects. Utilizing an improved deep learning object detection and multi object tracking algorithm with added attention mechanism to extract foreground moving targets in videos, and using a mixed Gaussian background modeling algorithm establish a background, laying a stable target foundation for subsequent video concentration. At the same time, design trajectory recombination optimization methods to ensure that the targets do not overlap as much as possible. Reasonably place the targets in the new condensed video sequence, determine the index of all targets in the new condensed video stream, and finally integrate each frame of target images into the background image according to the set index rules, ultimately obtaining the synopsis video.
Virtual currency trading strategy based on ARIMA and AHP-PSO
Authors: Song Hongru , Zhang Zijie
Published: April 2023

As the price of virtual currency fluctuates greatly, precise prediction and appropriate trading strategies can bring investors best returns. This paper predicted the price of Ethereum and Bitcoin in the light of autoregressive integrated moving average model (ARIMA) and get a R2 of 0.995 and 0.993 respectively, which indicates the model can yield reasonable predictions. Then their investment ratios are set to 0.88 and 1.12 respectively by analytic hierarchy process (AHP). Particle swarm optimization (PSO) is used to solve the daily revenue function formed by the predicted price and the current price. Finally, the paper compared the returns yielded by the PSO trading strategy optimized by AHP and the strategy without optimization. It can be concluded that the AHP has a possibility of 64.66 per cent to yield more returns when used.
The Impact of Foreign Direct Investment (FDI) on Urban Economic Resilience: An Empirical Study Based on the Yangtze River Delta Urban Agglomerations
Authors: Zhang Tianyu , Liang Zhixuan , Wang Binyu
Published: April 2023

Urban economic resilience can reflect whether cities can sustain high-quality development. Therefore, based on the panel data of 26 cities in the Yangtze River Delta Urban Agglomerations from 2010-2019, this paper measures the city economic resilience index using the entropy method and explores the impact of foreign direct investment (FDI) on the economic resilience of cities in the Yangtze River Delta using the Tobit model. The results show that (1) Shanghai, Hangzhou, Nanjing and Suzhou have higher urban economic resilience than other cities and are more likely to achieve high-quality economic development (2) FDI has a significant negative impact on urban economic resilience (3) the level of urban innovation development can promote the development of urban economic resilience; urban freight capacity, urban greening level and advanced industrial structure hinder the development of urban economic resilience, but the effects of urban greening level and advanced industrial structure are not significant. Finally, this study makes several suggestions on how to improve the economic resilience of the Yangtze River Delta Urban Agglomerations.
Research on the influence mechanism of child dependency ratio on household saving rate
Authors: Wang Jiaying , Wang Sijie , Lin Xiaorong
Published: April 2023

High family savings rate has always been an important feature of China's economy. With the gradual opening of China's birth policy, the high family savings rate is closely related to children's dependency ratio. Based on the data of CFPS in 2018, the regression results show that: first, the child dependency ratio enhances the precautionary savings of families and increases the household savings rate; Second, generational care makes the parents' lasting income more stable, so under the condition of the same child support ratio, households with generational care have a lower savings rate; Third, the ratio of child dependency in eastern and western families has a significant positive effect on saving rate, while the central region has no significant effect. Finally, it puts forward some suggestions on strengthening social security, advocating intergenerational care and narrowing the gap between East and west China.
Comparative Analysis of macroeconomic between China and the United States before and after the COVID-19 pandemic
Authors: Xi Yirong
Published: April 2023

As the two largest economies in the world, China and the United States together account for more than 40% of the world's GDP. Since the outbreak of the COVID-19 epidemic in 2020, whether the economic development of China and the United States has been affected by the epidemic, the degree of impact and the degree of economic recovery have attracted worldwide attention. This assay collects macro indicators such as GDP, unemployment rate and CPI in China and the United States in the past five years from the official websites of the U.S. Bureau of Labor Statistics and the National Bureau of Statistics of China. Combined with the research results of existing scholars, a comparative analysis of the economic conditions of the two countries before and after the epidemic was carried out. It is found that in 2020, when the economies of the two countries are affected by the epidemic, the relative decline is smaller and the decline in the United States is larger; when the economies of the two countries rebound in 2021, the absolute level of China's economic growth is significantly higher than that of the United States, but the relative recovery is smaller than that of the America is bigger. In the post-pandemic era, the United States has experienced staggering inflation. After the problem is found, this assay explains the cause of the problem and proposes a solution.
The Economic Impact of Monopolistic Advantage: A Case Study of Microsoft
Authors: Shao Fuqiang
Published: April 2023

As one of the largest company in the world, Microsoft is regarded as a monopolist because of its dominant position in operating system and software industry form 1990s till now, and this kind of monopoly is going to be sustained in the future. Under a such background above, it is important for customers to know what impacts do monopolist have on them. Is it benefit or doing more harm to customers when compared to competitive corporations. In this paper, we use Microsoft case analysis to discuss questions like product quality and customers’ economic burden of monopoly. Also, specific data such as customer satisfaction, income and expenditure are used to help solve the problems. We find that what really matters about the quality depends on the attitude and thoughts of customers who purchased and experienced the products since Microsoft’s main products had been recognized by public according to their significant market share. However, monopolist does has negative impact on customers in some way. After analysis, we offer some suggestions on how Microsoft or other monopoly companies can improve their customer satisfaction and what measurement can be used to change the present situation.
Analyzing the impact of monopoly industry on labor force based on an economic model which is profit maximization -Take takeaway platform monopoly as an example
Authors: Wang Siqin , Wang Yeting
Published: April 2023

In this era of rapid Internet advancement, the platform economy is getting bigger and bigger and moving towards monopoly. Under the control of capital, firms maximize their profits by undermining the interests of workers. This paper uses theoretical and data analysis to explore the business strategies that companies choose to maximize their profits and the impact on labor under the monopoly of companies. We concluded that the take-out platforms are centered on "more work, more pay". By studying the benefit distribution model and scheme of the platform, we analyze the impact of the take-out platform on the riders while maximizing their own revenue. Microeconomics is used as a basis to analyze the negative impact of companies in monopolistic markets on the labor market and the labor force in the market that is monopolized by buyers. The government needs to improve the management terms and anti-monopoly is also very important to control and sanction the behavior of takeaway platforms to bring more protection to the rights of riders.
Research on Debt Financing Strategy of New Energy Vehicle Enterprises: Taking BYD Company as an Example
Authors: Chen Peihong
Published: April 2023

With the rise of the new energy vehicle industry, the demand in the automotive market has increased dramatically. As a leading company in the new energy vehicle industry, Byd Company Limited (BYD) ranks among the top in the world in terms of sales and has good development prospects. However, there are still uncertainties in the recovery of the global economy, the normal operation of auto companies is affected. In recent years, BYD's debt costs are increasing year by year, but its debt capacity has not improved significantly. The rational use of working capital, optimization of debt structure, improvement of debt capacity, and prevention of debt risks are urgent tasks. This paper adopts the methods of literature review, case study and data analysis, based on the debt maturity structure theory, to analyze the debt structure, debt capacity and debt risk of BYD Company. It is of great significance for the current new energy vehicle enterprises to carry out debt financing.
Fintech and the Digital Transformation of Financial Services
Authors: Qi Yanli
Published: April 2023

By creating a decision-making mechanism that relies on data as the basis for decisions, fintech is accelerating the change in the financial sector. The financial markets have faced numerous possibilities and problems as a result of their continuing rise. Fintech is a broad term that can refer to anything from straightforward mobile payment apps to intricate blockchain networks that process cryptocurrency transactions. This paper reviews the literature on the continuous development of fintech and investigates how it is altering financial markets by gathering pertinent data for in-depth study. It has been discovered that fintech is a two-edged sword for the financial markets. Many sectors now have access to comprehensive and up-to-date decision support information as a result of its development and utilization. But at the same time, traditional financial services are replaced by new technologies such as the Internet, and the complexity and risk brought about by fintech will also manifest itself.
The effect of operation systems on consumer population in smartphones market
Authors: Bei Qiaozhu , Huang Wanru , Wang Yichang , Xiong Shuaiyan
Published: April 2023

Individual reliance on smart devices such as mobile phones have seen exponential increase in the modern age. Customers now have a wide variety of brand choices, some brands like Samsung and Apple are world-wide products to consumers. Yet, there are only two widely applicable smartphone operation system, which is iPhone’s iOS and Android OS. The population of these operation systems are different, in order to figure out what cause the preference of the consumers, we use three measuring points to infer the reason.
Research on Technology Innovation and Income-generating Efficiency of Enterprises from the Perspective of Science and Technology Management
Authors: Cao Ze , Li Minghui , Wang Ben , Lv Peihua
Published: April 2023

Under the background of technological innovation, enterprises gradually attach importance to building an innovation ecosystem to improve innovation and income-generating efficiency. However, how to carry out technological innovation in order to improve the efficiency of scientific and technological income generation is the key problem of enterprise innovation ecosystem research. In view of the relationship between technological innovation and income-generating capacity of science and technology. Based on the analysis of the difficulties of science and technology management, system dynamics and Pearson correlation method were adopted. From the perspective of qualitative and quantitative, the influence degree and relationship between science and technology innovation and income generation were analyzed. The results show that R & D investment and innovation platform are significantly positively correlated with corporate technological income. This paper puts forward the idea and implementation path of scientific and technological innovation management, and provides reference for technological innovation and income generation of enterprises.
Research on the Effectiveness of Network Agenda Setting of Tourism Destination Image Dissemination: Take Ganzi as an Example
Authors: Zhang Yuan , Jing Yuxin
Published: April 2023

This paper selects the push articles of the WeChat public account of Ganzi County Tourism. From the perspective of the media communication effect, based on the network agenda-setting theory, the media agenda and the public agenda are compared and analyzed. The research proves that the public agenda of Ganzi's tourism destination image is significantly related to the media agenda, which shows that the media has the agenda-setting ability in destination image communication. This result verifies the network agenda-setting theory in the tourism destination image display. It has a certain reference value for the study of the effect of network agenda-setting.