bluuebunny/crossref_metadata_2025 huggingface dataset:
The Phenomenal Class Teaching to Individual Learners
Authors: DeFehr Wayne
Published: April 2023

This paper investigates some of the practical implications of a phenomenology of education, exploring how this philosophy can have a daily application to work that takes place in the classroom. Beginning with an overview of key principles in the philosophy of phenomenology, including ideas from Edmund Husserls and Martin Heideggers writings in the 19th-century, the paper examines more recent applications of this philosophy as an approach to pedagogy. The discussion includes the work of Malte Brinkmann and Norm Friesen, and then also that of the philosopher Hubert Dreyfus to consider the ways in which phenomenology would shape a teaching practice. The challenge here involves attempting to form authentic and genuine relationships, despite, or through, the various education technologies and platforms that are available these days. These technologies are often promoted as leading to student immersion in the subject matter, while the reality is, at the same time, that the teacher becomes distanced from the students, through the mediating effect of all this media. One example that is proposed as a way to address this issue, involves discussing the example of a class that I teach, where the students need to collaborate to build a playable video game in RPG Maker MV. They become immersed in learning the technology required to create an interactive game, while at the same time remaining in contact with their fellow collaborators as they develop the narrative and game play along the inclusive and enriched story telling principles that are presented in class.
Research on the Influence Mechanism of Corporate Social Responsibility on Consumer Behavior from the Perspective of Attribution Theory
Authors: Liu Ying
Published: April 2023

Since prior studies did not focus a lot on the influence mechanism of CSR on consumer behavior from the perspective of consumers, this topic needs to be further researched. Based on the attribution theory, this study takes Hongxing Erke as the representative case using grounded theory to explore the influence mechanism of CSR on consumer behavior. This research finds that CSR strength, CSR consistency and brand image are the three main conditions that affect consumers' attribution pattern, and consumers' perception of marketing is the boundary condition that affects consumers' attribution pattern. Attribution can be divided into prosocial and self-interest. Prosocial attribution has a positive effect on consumers' purchase intention, while self-interest attribution has a negative effect on consumers' purchase intention. This study has certain guiding significance for enterprises' marketing strategy and CSR implementation.
The Main Factors Contributing to Chinas FDI
Authors: Gao Zheng , Li Xinye , Mo Yu , Wang Jiaxing
Published: April 2023

According to the data recently released by OECD, the world's foreign direct investment showed a significant decline of 42% in 2020. However, China's FDI rose against the trend, becoming the world's largest foreign capital inflow country for the first time, and surpassing the United States. This paper uses the data of the Chinese National Bureau of Statistics and Wind data to analyze the main factors contributing to China's FDI. The results show that in the overall multiple linear regression, only the ratio of exports and imports has a negative correlation with FDI, the ratio of foreign trade to GDP, population, and the number of international firms have positive and the trade war between US and China and Covid-19 pandemic are not significant for FDI, the coefficient of two variables is both negative. For the multiple linear regression by year, the significant influencing factors in different years are different and show volatility.
The Governance Effect of China's Green Finance Policy from an International Perspective
Authors: Liu Yuan
Published: April 2023

Most of the previous studies on the utility of green financial policies have focused on provincial data, exploring the differences between different provinces at the same time; few have focused on China as the main body, focusing on the positive effects of national-level green financial policies on the rapid development of the economy and society effect. Based on the macro data of 43 countries, this paper uses the SBM model of undesired output to measure the main characteristics of social and economic development. It estimates the net effect of China's green financial policy through the non-parametric synthetic control method. The study found that China's green financial policy has a significant positive effect on the improvement of factor productivity. Further exploration of the predictor variables shows that China's industrial structure and technical level are relatively low, and the use efficiency of green financial funds and government green finance need to be optimized.
Research on the Influence of Pension Insurance on the Chinese Elderlys Subjective Well-Being Based on Maslow's Hierarchy of Needs
Authors: Fang Wang
Published: April 2023

The acceleration of population aging is a basic national condition in China. To ensure the living condition of the elderly is a strategic issue. Whether pension insurance plays a role in promoting the subjective well-being of the elderly has attracted widespread attention. This paper explores the degree and mechanism of the influence of current pension insurance programs in China on the subjective well-being of the Chinese elderly. The research significance of this paper lies in helping to provide a theoretical basis for relevant policy recommendations in the future. On this basis, this paper searches the literature on CNKI for research materials. Combined with their research questions, 21 articles from the past 20 years are selected to analyze the influence mechanism of pension insurance on the subjective well-being of the elderly, using Maslow's hierarchy of needs as the theoretical basis. The results show that pension insurance has a certain contribution to the subjective well-being of the elderly, acting in economic, psychological, and social aspects, respectively.
Research on NBA Marketing Strategy Optimization based on the Chinese Market
Authors: Xiong Tianyou
Published: April 2023

With the approach of globalization to the world, human is crossing spatial barriers and hierarchical and cultural restrictions. As a result, we are gradually becoming more united because of globalization. And as such issues reach all aspects of peoples lives, humanity has entered a whole new era. However, since Covid-19, everything around us has been changing. The service industry is impacted the most because they need people to gather, which is not allowed during such period, and thus the depression of these companies begins. In this case, the writer chose the most popular company, NBA, the most influential sports company affected by Covid-19 recently. The writer provides several effective solutions to solve this problem, such as using international media, attracting the best foreign players or teams, and a globalized licensing trademark strategy, which is provided based on the literature research method, survey method, and comparative method. In addition, because the epidemic came so abruptly, there is very little literature on the web about how to help the NBA come out of it the epidemic. Most of them discuss the NBAs marketing strategies or compare the gap between the CBA and the NBA, so this article plays a small role in helping the NBA eliminate the Covid-19 impact.
Shariah Compliance: An Empirical Study on the Perceptions of Islamic Financial Institutions in Pakistan
Authors: Munir Dr.Sahar , Saleem Sana , Majeed Muhammad Imran
Published: April 2023

This paper examines the importance of Shariah Compliance for Islamic Financial Institutions (IFI) in Pakistan along with the process followed to ensure it. Islamic Banking was initiated in Pakistan in early 2000s and by now a proper network exists with a market share of 13.6 % of Assets and 14.7% of deposits with a network of 21 Islamic Banking institutions, out of which 5 are full-fledged Islamic Banks and 16 conventional banks have standalone Islamic windows. This study contributes as being first of its nature to study the Shariah compliance in the context of Pakistan. For the study, mainly primary data was used. Interviews of Shariah Compliance Heads and Shariah Advisors were conducted. The results indicate that a Shariah Compliance acts as a vital element for Islamic banking in Pakistan and influences the operations carried out by them. Moreover, a proper Shariah Governance System is also implemented and followed by the Islamic Financial Institutions. In addition to this, Shariah Advisors also play a pivotal role in the whole procedure and are responsible for Shariah Compliance in the IFIs.
Correlation Between Stock Returns of Wine Corporations and Weather Conditions
Authors: Li Yijie , Xin Wen
Published: April 2023

Among determinants of wine spot prices, the weather is one of the most influential factors. Previous studies have confirmed the spot price of fine wine is correlated with some weather variables, such as the air temperature. Also, much research illustrates some weather conditions are related to the stock market. In this paper, we focus on the correlation between some weather variables as main determinants of wine prices and the stock returns of wine companies which are listed on NYSE. We have several conclusions: (1) return of equity of wine companies has a negative correlation with the level of precipitation; (2) results are more significant when controlling years; (3) the level of precipitation has greater negative impact on returns during planting season of grapes; (4) the odds of having positive returns in planting season is lower than non-planting season.
Analysis of the Factors Affecting the Price Fluctuation of Bitcoin
Authors: Deng Wanying
Published: April 2023

According to the monetary theory, this paper believes that the demand for Bitcoin mainly includes two aspects: transaction demand and investment demand. This paper further discusses the impact of different demands on the price of Bitcoin based on two aspects of demand. Transaction demand and investment demand together affect the supply and demand relationship of the Bitcoin market. The empirical results show that the volatility of Bitcoin price is higher than that of international currencies and stocks as investment tools. This article emphasizes that the price of Bitcoin is primarily affected by supply and demand.
Research Progress of Information Asymmetry in Recent Ten Years
Authors: Fang Junxin
Published: April 2023

The assumption of information is the basis of all basic financial ideas (net present value, portfolio theory, capital structure and option pricing). The assumption of information is often inseparable from information asymmetry. Information asymmetry is a rich and diverse content, which can be connected with many fields. Asymmetric information may hurt sellers with more information and superior products, such as agent problems. Research at home and abroad shows that information asymmetry will cause many problems, but there is a lack of specific research evidence. In recent ten years, information asymmetry has had a great impact on both business society and daily life. This article reviews the relevant literature and summarizes the phenomenon of information asymmetry at home and abroad in the recent ten years, so as to increase the understanding of information asymmetry and lay a foundation for the trend prediction of information asymmetry in different environments in the future.
Research on Improving China's Agricultural Development Through High-quality Elderly Labor
Authors: Peng Xiuyun
Published: April 2023

Based on nowadays China's aging population and unbalanced development between urban and rural areas, rural revitalization of the urgent need of development of the status quo, reasonable hypotheses and research, this article through to the National Bureau of Statistics released data of population and the related literature research, as well as on the investigation to the actual situation that the resources of high quality senior citizens can reasonable use to some extent to reduce resource waste, and promote social development.
Analysis of the Correlation Between Executive Compensation and Corporate Performance in Listed Companies
Authors: Zhang Xiyuan
Published: April 2023

This paper selected a sample of US listed companies and conducted correlation analysis and regression analysis on the relevant data of the sample 2021 with the help of Excel and SPSS statistical software in order to clarify the degree of correlation between executive compensation and corporate performance of listed companies. The findings suggest that the two are not correlated, but the reason for this result may be due to the influence of the irresistible general environmental background and the imperfection of the listed companies' executive compensation policies. In order to improve corporate performance, some suggestions are made so that both companies and executives can achieve a win-win situation.
Insights into Cryptocurrency Market Prices Fluctuation Correlated to COVID-19 Pandemic spillovers: Whether Bitcoin Can Act as a Safe Haven
Authors: Wu Maoyuan
Published: April 2023

In this article, I examine the relationship between COVID-19 daily additional cases and Bitcoin daily closing prices by applying Quantile-on-Quantile Regression (QQR) approach. The results reveal that the changing intensity level of COVID-19 does have an impact on Bitcoin prices. Whats more, my research captures the dependence between the distribution of Bitcoin prices and the severity of the COVID-19 pandemic. Levels of COVID-19 cause a rise in Bitcoin prices. I give a fresh look at combining every day confirmed number of new infections of COVID-19 and behavioral economics with fluctuating daily Bitcoin prices. And as the confirmed case has stabilized, although it is still at a relatively high position, investors would develop speculative psychology and take abnormal and seemingly inexplicable actions, e.g., they prefer to invest in Cryptocurrency rather than hold US dollars cash. Bitcoin offers a relatively steady performance in enduring the pandemic shocks; thus, it can be considered a safe-haven asset.
Mean-Variance Application of Portfolio Management in Hong Kong Stock Market
Authors: Li Qingan
Published: April 2023

The Hong Kong stock market is one of the world's top financial markets, and some investors want to gain benefits by investing in the Hong Kong stock mar-ket. Some studies have found that reasonable asset management can effectively reduce risks and increase returns. Therefore, the research topic of this paper is the importance of investment portfolio for investors to profit in Hong Kong stock as a financial market. The research methodology of this paper is as follows: firstly, we collect the data of Hong Kong stock market, secondly, we organize and combine the data, and use the mean variance model to calculate the maximum return and risk under the asset portfolio. The results show that the portfolio can effectively improve the return and risk value of investments. The E Commerce and Internet Services sector has always been a large part of the portfolio and can be a prime target for investors.
Research on Marketing Strategy of the Game CompanyTake Nintendo as an Example
Authors: Yu Jiatong
Published: April 2023

With the development of network technology, games have become a relaxing form of entertainment for people. There are a lot of games that people love, and successful marketing is a big part of that. This paper will review the previous research results adopting Nintendo game company as an example to analyze and study the marketing strategy of game companies, and provide some reference suggestions. This paper will start from three basic points: 3C's (Customer, Competitor and Company), STP (Segmenting, Targeting and Positioning) and 4P's (Product, Price, Place and Promotion) to explain Nintendo's marketing strategy. This paper analyzes Nintendos marketing strategy and the accurate positioning of products and customers. It is sound and successful.
A Study on the Impact of Chinese Monetary Policy on Enterprises' Accrual Earnings Management
Authors: Kuang Yanni
Published: April 2023

As one of the important means for enterprises to carry out accrual earnings management activities, which mainly relate to the adjustment of accounting estimates and the use of accounting policies to make the values of relevant accounting subjects meet the needs of enterprise managers and reach other stakeholders expectations. This paper empirically examines the relationship between changes in monetary policy and corporate accrual earnings management activities, by taking A-share companies from 2010 to 2020 in Shanghai and Shenzhen stock markets as the sample, and by classifying accrual earnings management activities into positive and negative, it more accurately captures the choice of accrual earnings management activities that companies tend to adopt in different periods. At the same time, this paper also analyzes the influence of ownership attributes on the management behavior of companies' accrual earnings management under different monetary policies from two aspects: state and non-state. By studying the influence of monetary policy on corporate accrual earnings adjustment, this dissertation is not only a supplement to previous researches on earnings management and monetary policy, but also points out new ideas for future research.
Mean-Variance Model Theory and Its Application in Chinese Stock Market
Authors: Lin Zhanfeng
Published: April 2023

This paper examines the effect of the mean and modeled mean volatility on the mean curve of a Markowitz portfolio analysis of major values and simultaneous changes. The average investment value in the future and the predicted trend curve change, the actual effective model mean and the actual volatility are the volatility shown in todays Mavitz. The Kowitz portfolio model of volatility yields the horse trend curve under changing conditions.
Research on the Impact of New Energy Vehicles on Chinas Industrial Policy Innovation
Authors: Peng Jingyao
Published: April 2023

The subject of Chinas new energy vehicle policy implementation analysis was chosen due to the growing importance of switching to renewable energy due to resource depletion, price volatility, and the need to address pressing environmental issues. New energy vehicles are critical for controlling greenhouse gases and atmospheric pollutants, reducing the auto industrys dependence on oil which makes this subject matter crucial nowadays. Such methods as secondary literature analysis and case study are essential to analyze the processes behind Chinas new energy vehicle success. As a result, the current backdrop of environmental and political instability has stimulated the Chinese government to create a range of policymaking initiatives that rely on provincial and central collaboration, cutting switching costs, and socially normalizing new energy vehicle use. The value of this paper is in how it can be utilized as a fundament for other business branches and governments to construct effective initiatives to grow the renewable energy vehicle market.
Influences of Customers Nostalgic Proneness on Their Brand Cognition Based on the ABC Model of Attitude
Authors: Cunqi Bian
Published: April 2023

As the economic environment and social culture change dramatically, nowadays there are numerous opportunities for the nostalgic brand in China to regain competitive advantages. Grounded on the affective, behavior, and cognition (ABC) model of attitude, this paper aims to clarify the relationship between customers nostalgic proneness, purchase intention, and brand cognition to explain the mechanism of nostalgic consumption. Taking the big white rabbit brand as an example, a structural equation model was used after the constructs were empirically confirmed by reliability and validity tests. Customers nostalgic proneness is found to be positively correlated with their brand cognition and the nostalgic brand is advised to fully exert its potential.
Stranger Online Social Media Operation and Strategy: Case Study of Tantan App
Authors: Feng Peiyuan
Published: April 2023

With the advancement of the Internet and technology, the types of social media software are constantly expanding. Recently, a new kind of social software has gradually emerged in the market. This is stranger dating software. Unlike Facebook, Instagram and WeChat, which are more used to communicate with familiar people, dating social software mainly aims to make friends with strangers. Its emergence is a change in the market. This article will analyze Tantan, the most popular dating software for strangers in the Chinese market, explore its development background, understand its business model, and analyze how it grasps user needs for marketing.
Application of NPV and IRR for One Project in Tianchang City
Authors: Qian Yuchen , Xu Nuo , Yang Wei , Yao Xiao
Published: April 2023

NPV and IRR assessment methods currently play a key role in the financial investment field. This paper selects the cash flow data of the first year of the project The seventh round market operation project of Urban Environmental Health Service (East District) of Tianchang City, that is, the cash flow statement for 12 months in 2021. With a planning period of four years, the project has been in operation for more than a year, but it lacks project evaluation. Therefore, we chose the NPV and IRR methods to evaluate the project to provide a reference for the subsequent project development of the company. The results suggest that this project is not performing well and deserve further investigations.
Application of Three Commonly Used Portfolios in the Hong Kong Stock Market
Authors: Luo Junwen
Published: April 2023

This paper will use stocks in Hang Seng Index to figure out the construction of portfolios. In addition, Fama experiment would be used to eliminate the idiosyncratic risk and R language would be regarded as the tool to do onerous computation. And 9 stocks randomly selected plus one risk-free asset would be entailed to construct portfolios, and finally all the stocks without missing values would be entailed. This paper may shed light on investing combination of stocks of Hang Seng index or some others about how to assign the weight proportion to reach different purposes.
Research on the Impact of Financial Technology on the Performance of Chinese Commercial Banks Taking the Retail Transformation of China Merchants Bank as an Example
Authors: Zhu Yiting
Published: April 2023

In the era of big data, the integration of financial services and science and technology has become a trend, and financial technology has become critical to the financial service industry. This paper takes China Merchants Bank as a representative case study, summarizes the transformation process of China Merchants Bank business, and sorts out the aspects and transformation measures of China Merchants Bank's use of financial technology. By analyzing the case of China Merchants Bank introducing financial technology to realize the transformation, this paper uses the method of financial index analysis to study the impact of financial technology on the transformation of China Merchants Bank, obtains the impact of financial technology on commercial banks, and puts forward appropriate suggestions.The innovation of this paper is mainly reflected in the research methods and directions. According to the comprehensive literature, there are few cases of domestic and foreign scholars studying the combination of commercial banks and fintech. Therefore, this paper adopts the method of combining theory with practical cases, starting with the promotion of financial technology transformation by China Merchants Bank, discusses the impact of financial technology on the performance of China Merchants Bank, and then gives strategic suggestions for other commercial banks to use financial technology.
The Predictive Power of Implied Volatility and GARCH Forecasted Volatility During the COVID-19 Pandemic: Evidence from Chinas Stock Market
Authors: Zhang Wei
Published: April 2023

In this study, we explore how the performance of several popular historical and forward-looking forecasting measures for equity index volatility is affected by the COVID-19 related uncertainty. Our findings present convincing evidence for the advantages of implied volatility in predicting future volatility in the context of the COVID-19 pandemic. Our results also reveal that GARCH forecasted volatility contains unique information about market risk, but the information efficiency is sensitive to economic uncertainty. Therefore, the empirical evidence from Chinas stock market is supportive of a popular theoretical view that GARCH and implied volatility capture different aspects of market uncertainty and an appropriate combination of both measures may perform best in terms of information efficiency. This article contributes to the stream of postCOVID19 literature on its impact on financial markets and provides useful implications for financial practitioners.
The Time-varying Impact of the Covid-19 Pandemic on Biopharmaceutical Industry and Manufacturing
Authors: Yuan Zhihao
Published: April 2023

The pandemic has affected the world economy, specifically the manufacturing and biomedical sectors. This study examines the effects of COVID-19 on the yield and its volatility of manufacturing and biopharmaceutical indexes over a range of periods. It concludes that while the pandemic has had a short-term negative impact on the manufacturing index, the long-term effects on the biopharmaceutical industry outweigh any short-term fluctuations. But over time, the manufacturing index continues to represent its fundamentals. This paper aims to analyze the different short-term and long-term impacts of the pandemic on the biopharmaceutical index and the manufacturing index through data analysis.
Hedge Strategy Analysis and Financial Analysis of Volkswagen
Authors: Zheng Yuqi
Published: April 2023

Good hedging strategies need to thoroughly analyze the financial situation, risks, and market changes faced by the company, and then make reasonable choices based on the actual situation. After this article analyzing various financial indicators of Volkswagen, it can be found that the stock price of Volkswagen fell to the bottom in 2020, then quickly recovered in 2021 and reached a peak in the observation period. This includes market factors such as Covid-19 and price fluctuations of raw materials, the recovery of Volkswagens profits in 2021, and the hedging strategies like using interest rate derivatives made by Volkswagen Group in 2020. Although this article concludes with some shortcomings of its hedging strategies, overall, this company's hedging strategies are still very instructive, and in the future, it is promising to propose effective, value-conscious hedging strategies to transform the company's risks into opportunities to increase shareholders value so that the company can be more flexible to face some risks.
Analysis of Branding and Online Marketing Strategies for Cultural Heritage
Authors: Wang Jiayin
Published: April 2023

Cultural heritage, as an important part of a country's culture, is receiving more and more attention and branding has become an important tool in the process of preserving it. The paper uses literature research and quantitative analysis to analyze the branding of cultural heritage and the online marketing of cultural heritage. The analysis results show that there are different brand paths for different types, forms and characteristics of cultural heritage. However, it is necessary to combine the characteristics of the cultural heritage itself, and deepen the impression in the minds of consumers through brand design. At the same time, use the interactivity, aggregation and precision of the Internet to improve marketing efficiency. This paper carefully sorts out the existing research from two dimensions, and strives to summarize the common methods and network marketing strategies of Chinese cultural heritage brand promotion. The research results can stimulate relevant enterprises to produce more and more effective network marketing tools and obtain economic benefits from them. At the same time, it provides a feasible path for the protection of Chinese cultural heritage.
The Impact of Chinas Independent Director System on Corporate Financial Fraud: The Case of Kangmei Pharmaceutical Fraud
Authors: Liu Siyang
Published: April 2023

The case of financial fraud of Kangmei Pharmaceutical is known as one of the most serious fraud cases ever in A-share. This paper analyzes the cause, course, and result of the financial fraud of Kangmei Pharmaceutical. Data analysis of the share price of Kangmei Pharmaceutical is conducted to investigate the impact of this incident on the market. The case study method, information asymmetry theory, and principal-agent theory are used to illustrate the impact of independent directors in the financial fraud case and the insights from the fraud case of Kangmei Pharmaceutical.
XGBoost-Based Human Activity Recognition Algorithm using Wearable Smart Devices
Authors: Ge Runchan
Published: April 2023

With the popularity of wearable smart devices, human activity recognition (HAR) based on smart sensors has been widely applied in daily life and medical health fields. In order to balance the accuracy of HAR and the complexity of the algorithm, this paper proposes an HAR algorithm based on the extreme gradient boosting (XGBoost) method. The original data collected by sensors contains noise, thus denoising process is firstly performed. Then multi-dimensional features are extracted from the data because of the limited dimensional features, which cannot be directly utilized in the training process. After that, principal component analysis (PCA) is used to reduce the dimensionality of the data in order to alleviate the input complexity of the training model. Finally, the human activity is recognized using the XGBoost method, and the ultimate goal is to obtain the tradeoff between speed and accuracy of the HAR algorithm.
Abstractive summarization of COVID-19 with transfer text-to-text transformer
Authors: Teng Zhaopu
Published: April 2023

As a classic problem of Natural Language Processing, summarization provides convenience for studies, research, and daily life. The performance of generation summarization by Natural Language Processing techniques has attracted considerable attention. Meanwhile, COVID-19, a global explosion event, has led to the emergence of a large number of articles and research. The wide variety of articles makes it a perfect realization object for summarization generation tasks. This paper designed and implemented experiments by fine tuning T5 model to get an abstract summarization of COVID-19 literatures. A comparison of performance was shown to prove the reliability of the model.
PT module -A Traffic Signal Classification Model Based on Convolutional Neural Networks and Random Forests
Authors: Ren Keyu , Peng Heqing , Wu Junwei , Yao Shengtao , Li Jinfeng , Li Pingyu
Published: April 2023

Autonomous driving and image recognition are the hot directions of Internet development nowadays. In self-driving cars it is necessary to capture traffic signs in front of the vehicle by cameras. To ensure that the information of image recognition is correct, a set of image classification models with high accuracy should be used to classify the recognized objects in order to determine the next instruction of vehicle operation. There were many achievements in the research work of traffic sign recognition, but there are still some shortcomings. By combining CNN and random forests with PT module (a module that can improve the accuracy of feature extraction), we finally came up with a classification model that can efficiently place the received traffic sign images into a specified category, which we obtained 97% accuracy on the GTSRB dataset, which is much more accurate than traditional neural network methods or regression methods. We have also evaluated it on other datasets and the results obtained are more promising.
Machine Learning based Terrorist Attacks Prediction Algorithm
Authors: Wang Yuanyuan
Published: April 2023

Terrorist attacks are spreading rapidly all over the world, which has caused heavy casualties and property losses. Therefore, it is very necessary to predict precisely the types of terrorist attacks and provide important information for counter-terrorism work. The existing research on terrorist attacks only analyzes a few characteristics, which leads to the limitations of the research. Therefore, this paper not only adds some continuous and discrete features, but also adds unstructured features based on the current research, which can accurately describe terrorist attacks. This paper proposes a random forest method based on threshold for feature selection because of the added characteristics of terrorist attacks, and then uses XGBoost model to predict the types of terrorist attacks. This method helps to prevent terrorist attacks and reduce the damage caused by terrorist attacks, and providedecisionsupport for the counter-terrorism department to take measures in advance.
A Novel Method for Text Classification Dealing with Local Data Structures and High Data Dimensionality
Authors: Zhong Weijia
Published: April 2023

Text categorization involves training models and making predictions over high-dimensional feature space. With the exponential growth on the amount of text resources on the Internet, the demand and difficulty of classifying digital text documents increases over the past decades. k nearest neighbors (kNN) has been proved to possess satisfying predictive power on text classification problems. However, kNN is sensitive to local data structures and its time cost is proportional to the product of the training set size and the feature space dimensionality. This paper proposes a novel text classification method called PCA pre-processed local correlation vector kNN (PCA-Local-CorVec-kNN) that applies PCA and kNN consecutively to the text datasets and introduces local correlation vectors to the sets of nearest neighbors produced by kNN. The proposed method has lower time cost than conventional kNN because of using PCA and is robust to local data structures since correlation vectors are introduced. Problems such as imbalanced datasets, choosing different k values for different samples, weighted voting are also tackled by the proposed method.
A Systematic Study on Intelligent Learning Techniques for Online Education
Authors: Li Jiayi
Published: April 2023

With the increase of the situation and reasons for staying at home, for example, the spread of COVID-19, online education at home has correspondingly been of increasing importance in our daily learning, covering not only academic education but also adult education. Compared with offline face-to-face classroom teaching, the online learning system can capture a lot of students' learning data, such as learning duration, class rate, class completion rate, etc., which can be applied in further education design. Based on these data, one can explore the possibilities to promote the development of online education, using techniques like machine learning and deep learning. Such efforts also provide educational institutions and teachers with more analytical solutions to problems, making intelligent education play a greater role in advanced education, and help students to improve their study effectiveness specifically. Nevertheless, there still lacks of a systematic study on the direction of this work, which hardly depicts the overall development. In this paper, we first try to bridge this gap by sufficient investigation and analysis. We have studied the mainstream efforts on Intelligent learning Online Education (called ILOE) from two different dimensions, i.e., technology and task types. For each dimension, we analyze the characteristics of related works. Furthermore, we also provide useful suggestions for the future improvement of ILOE.
Research on traffic congestion situation in urban central area based on SIR model
Authors: Chen Keyu
Published: April 2023

Urban traffic congestion is similar to the spread of infectious diseases. Based on this point of view, based on the classical infectious disease model SIR, a traffic congestion situation evolution model is established. The effectiveness of the model is verified by numerically solving the equilibrium point R0 and combining with specific examples. The model effectively depicts the process and characteristics of the dynamic evolution of traffic conditions in the central area of the city, which can help the urban traffic management department to make a real-time response to traffic congestion and provide reference for traffic management.
Hardware oriented bilateral filter algorithm and architecture survey
Authors: Gong Yao
Published: April 2023

Images and videos are often interfered with and affected by various noises. To filter out noise, researchers have proposed many filtering algorithms. bilateral filtering is a nonlinear filtering technique that can retain detailed information such as image edges well while denoising. However, it is a difficult task to implement fast and high-precision bilateral filtering algorithms in hardware platforms. In this paper, for the optimization of bilateral filtering algorithms, we analyze the gradient bilateral filtering and the piecewise approximate bilateral filtering algorithm that can be implemented in hardware, respectively. Then, we analyze and compare the implementation and optimization of bilateral filtering algorithms on FPGA and VLSI hardware architectures, and finally, make suggestions for choosing the appropriate bilateral filtering algorithms and hardware architectures for different purposes.
The Optimization Strategy of Deep Learning Algorithm Based on Image Recognition and Object Detection
Authors: Li Tailai
Published: April 2023

With the advent of intelligent era, the application of artificial intelligence has penetrated all walks of life in our daily lives and has gradually entered the scope of being understood by the public, such as AlphaGo, which is a human-machine game in Go. Meanwhile, with the increasing complexity of deep neural network algorithms, how to compress and optimize neural network models becomes the key to reducing model storage space and improving model deployment efficiency. This article will complete the INT8 quantization of the model for AlexNet and use the concept of batch normalization (BN) layer to prune the Yolov3 model. Finally, it is proved by experiments that the model quantization makes the image recognition time of the AlexNet about 1/3-1/4 of the original format; and pruning of Yolov3 will significantly reduce the storage space occupied by the model, moreover, make the speed doubled of embedded GPU real-time object detection. However, none of the three experiments reduces the model recognition accuracy. This paper proposes some essential concepts in the main body and applies them to model algorithms and experiments to provide theoretical support and proof for the field of deep learning model compression and optimization. Furthermore, it is possible to explore cutting-edge research directions like Sparse Convolution Net based on the research methods and experimental conclusions of the paper.
Sign Language Translation using Tensor Flow Model Zoo
Authors: Anilkumar Chunduru , E. Sathishkumar V , Pareek Pallavi
Published: April 2023

Communication is very essential for all humans because it allows us to share or express our sentiments, emotions, and other thoughts. Humans communicate with one another via natural language (for example words), body language (hand gestures, facial motions, and so on) or writing etc. People who do not have any impairment can easily converse with each other in natural language. However people with impairments, such as deafness or blindness, suffer a communication hurdle. They converse with common people by adopting sign languages, which are difficult for normal people to grasp or understand. People with hearing and speech impairments often have a very difficult time conversing with other people without any translator or interpreter. As a matter of fact, this research is being undertaken that transforms sign language into text that is easily understood by the ordinary individual. This system will identify numbers, alphabets, and hand gestures as well. Our primary purpose is to remove the obstacles that exist between the deaf, dumb, and the rest of people.
Sentimental Analysis on Product Reviews Using Support Vector Machine and Nave Bayes
Authors: Anilkumar Chunduru , E. Sathishkumar V , Kanchana Seepana , Kumar Sasapu Bharath
Published: April 2023

People nowadays use internet platforms to exchange ideas, share opinions, and learn online. Huge amounts of data are being poured into social media in the form of tweets, blogs, and updates on articles and items, among other things. The data is all unorganized and unprocessed. It is necessary to arrange and examine it. It takes a long time to analyze and process information using traditional methods and is impossible to analyze each and every sentence. So, there is a need to have a better approach. It can be done through sentimental analysis which extracts the opinion of a user in a piece of text data. This sentimental analysis will predict the polarity of the sentence, whether the given sentence is positive or a negative one. The sentimental analysis can be achieved through three approaches namely lexicon based, machine learning based and hybrid approach. This sentimental analysis is a part of NLP. This project aims to perform sentimental analysis using machine learning techniques and few natural language processing techniques on a product reviews dataset.
The Influence of Typeface and Case on Critical Care Systems Performance (Medical Ventilator)
Authors: Abrar Muhammad , Faisal CM Nadeem , Ahmad Haseeb , Ahmed Moneeb , Shahid Muhammad
Published: April 2023

Usability evaluation is a basic tool for investigating a system's performance in different environments. Many studies found a positive influence of different user interface aesthetics and their organization on usability ratings. These design aspects are one of the most important characteristics of systems usability, and few empirical studies have been examining the importance of typography specifically for safety-critical systems. This study aimed to investigate how different typographic factors, i.e., typeface and fontcase, influence a user's performance in health care safety-critical systems. Different study variables were considered, including task completion time, reflection time, and the total number of touches. To test the study objectives, the Hamilton-c6 ventilator prototype was developed. The experiments were conducted on 15 participants, including male and female physicians, in a controlled environment from different healthcare venues. A well-known technique, one-way ANOVA, was used to assess the data. The results suggest a significant difference between serif (times new roman) and sans serif (Calibri) groups for task completion time; in addition to that, the difference between fontcase groups (sentence case, lowercase, and uppercase) was not statistically significant. Moreover, this study investigated the pairwise influence of different typeface and fontcase groups. The results show a significant difference in task completion time. The descriptive analysis of different groups shows that the times new roman with the upper case group has the lowest task completion time while the Calibri with the uppercase groups have the highest task completion time. This study may pave a good research direction to explore the impact of these and other aesthetic factors in multiple contexts.
Research on Image Generation Methods Based on Adversarial Neural Networks
Authors: Ding Renjie
Published: April 2023

Image generation has become a heated research topic in recent years owing to its wide landing scenes and great potential in all walks of life. Especially after the emergence of adversarial neural networks, both the training process and results have been greatly improved compared with previous model methods. This paper focuses on the advantages of directly using Generative Adversarial Nets (GAN) to generate images, as well as its main problems: training instability, pattern collapse, and global correlation, and introduces the strategies and skills of subsequent improved GAN for these problems. Through experiments, we compare the improved network with the original GAN and try to combine the core strategies of these networks. In the experiment, the image quality generated by the combined network is higher.
Secure Electronic Commerce Transactions Using Pythagorean Triple-based Cryptography and Audio Steganography
Authors: Gabriel Arome Junior , Awosola Emmanuel Akindoyin
Published: April 2023

The rapidly increasing utilization of Information Technology (IT) in electronic commerce and other aspects of human existence has led to a rise in worries about the privacy and safe-ty/security of those involved. Due to the alarmingly high frequency with which data or user privacy breaches occur today, conducting online transactions can represent a major threat to buyers (and even business owners') privacy. Existing solutions to these security issues are still vulnerable to classic phishing scams. As a result, the construction of a robust and effi-cient audio steganography system for secure electronic commerce transactions is presented in this work. The developed system first encrypts sensitive financial data using the Pythagorean Triple-based Cryptographic (PTC) algorithm, then compresses the resulting cipher-text using the Lempel Ziv Welch (LZW) and Huffman's Compression Algorithms, and finally embeds the compressed file (using one-dimensional Discrete Cosine Transform (DCT)) in a suitable audio-file cover to produce an output (stego file) that is indistinguishable from the cover file. This output can then be exchanged between communicating entities across open networks. The new system has a little or no alteration in its outputs, as evidenced by the Signal-to-Noise Ratio (SNR), in the experimental results gotten.
Tomato leaf diseases classification using alexnet
Authors: Deepa D. , Yaswanth R. , Kumar K. Vasantha
Published: April 2023

The economy is largely reliant on agricultural productivity. Plant diseases and pests are also a serious issue in agriculture. It is necessary to recognise them early on in order to eliminate all infections as rapidly as possible and avoid crop devastation. To protect the plants against illness, a variety of insecticides have been utilised. Despite these precautions, the illness continues to spread throughout the field. Because we don't always know what kind of sickness we're dealing with, a bad pesticide may have been applied instead. As a result, it's all futile.Tomato leaf infections, on the other hand, are a severe problem for many farmers, thus mastering the severity of diseases in a fast and precise manner is critical to assisting staff in taking additional intervention steps to prevent plants from becoming more afflicted. An Alexnet model for detecting tomato leaf disease is proposed in this study, which may minimise the number of training processes while enhancing computation accuracy and gradient flow. This indicates that categorization of diseases is equally important. An improved classification model is presented in this paper for identifying and categorising tomato leaf disease. Before CNN is used to identify the pictures, a training dataset containing a large number of images is utilised, and visual characteristics are extracted using several methods. The Alexnet model achieves the highest classification accuracy when compared to other models.