bluuebunny/crossref_metadata_2025 huggingface dataset:
Data Visualization and Prediction for Telecom Customer Churn
Authors: Yang Pulin
Published: April 2023

With the deepening of telecom industry reform and the intensification of competition, the customer churn rate of telecom enterprises is gradually increasing. How to predict and effectively reduce customer churn is directly related to the survival and development of telecom enterprises. In order to effectively deal with unbalanced classification and improve the accuracy of high-value customer churn prediction in telecom industry, this paper uses telecom customer data set from kaggle platform to analyze people's use of telecom services, and help telecom operators find out the reasons for customer churn, and establish churn prediction model to reduce customer churn rate. In this paper, firstly, the data set is imported, and then the data visualization analysis is carried out. Then, the random forest model, SVM model and GBDT model are introduced for comparison. Experiments show that random forest has better classification performance than other methods, and improves the accuracy of high-value customer churn prediction.
The Advance of Ring Confidential Transactions
Authors: Jin Ruiqi
Published: April 2023

Ring Confidential Transactions (RingCT) is a protocol associated with the privacy-focused cryptocurrency Monero and is used to hide the transaction amount from the third party while still providing the confidentiality of the hide transaction. With the Pederson commitment scheme, ring signature, and other cryptographic constructions, RingCT plays a major role in making the transactions of Monero private. As a privacy coin, Monero has the unique property of fungibility in the cryptocurrency market from the protocols implemented. These protocols provided opportunities and challenges for its future. In this paper, the version of the protocol implemented in Monero is first inspected, including the commitment to zero and the range proof. Then, two critical cryptographic constructions used by RingCT 2.0, the accumulator and the signature of knowledge, are introduced. Finally, the influence of RingCT and other privacy features and the current situation of privacy coin is discussed.
Robustness Analysis of Traffic Sign Recognization based on ResNet
Authors: Li Kaiyao
Published: April 2023

Autonomous driving has always been an important research topic and application task of artificial intelligence, which has attracted the attention of a large number of researchers. As an important component of the environmental perception module in autonomous driving tasks, traffic sign recognition can help drivers understand road information in a timely manner and avoid potentially dangerous driving operations. To this end, accurate recognition of traffic signs is crucial from both a strategic and a practical point of view. The early recognition technology of traffic signs is mainly based on the detection of color and shape, whose recognition accuracy is limited due to the fading and deformation of traffic signs. Numerous researchers have successfully used these deep learning-based object identification algorithms for traffic sign detection and recognition thanks to the development of the Faster R-CNN and YOLO series algorithms. However, we argue that few efforts focus on the recognition performance of the model in different scenarios, which is especially important in the process of autonomous driving. Based on this observation, this paper first constructs the ResNet model. Part of the image recognition accuracy predicted by the model reached 99%. Afterward, the robustness of the model is explored by simulating complex scenes by changing illumination and noise, and it is proved that the model has good generalization ability and practical application ability.
Image Style Transfer based on DeepLabV3+ Semantic Segmentation
Authors: Zhang Jixiang
Published: April 2023

Image style transfer has always been a popular research method in the computer vision community, which aims to learn the style of a given image and the content distribution of other images to generate new images with both the above style and content. Thanks to the rapid development of convolutional neural networks, the accuracy, and visualization of image segmentation and migration have been continuously improved, but there is still the problem of local content distortion. Some recent works introduce the segmentation branch to obtain pixel-level content information in order to obtain a more perfect transfer effect. In this paper, we use the VGG19 convolutional neural network model to extract high-level feature maps representing image content information and perform image style transfer based on the DeepLabV3+ semantic segmentation network, which can move images to the same or similar semantic regions during the entire transmission process. In order to prevent content distortion after image migration, we also introduce an affine function to control the content change of the image during image migration. Extensive experimental results show that the method in this paper can further clarify the segmentation boundary and improve the semantic accuracy of the transferred image. In addition, we also evaluated the expectations of different individuals on the degree of style transfer. By distributing the survey, this paper demonstrates that the method described in this study results in better image quality, more in line with the expectations of the majority of respondents.
Improved Methods based on Too Many Cooks
Authors: Yuan Xiaotian
Published: April 2023

In the paper “too many cooks”, the authors developed a method called Bayesian Delegation to enable human-like coordination by inferring the sub-tasks of others quickly. However, some limitations which could be solved to improve the whole programme still exist in the partial work of the code. First, the implement of sub-task in terms of efficient actions or which agent(s) should work on it is not specified. Second, the sub-tasks may be finished in many different orders since the ordering of sub-tasks is partial and so agents probably have blank time. Third, with the increasing running times the action of different state could be recorded to improve the efficiency of the programme. So, this paper will focus on these three issues and try to solve them. In this work, some solutions to these challenges using Deep Q-Learning (DQN) and Bayesian inference are proposed. In the DQN experiment, value approximation has good performance in the simple multi-agents’ environment, the limitation that the implement of sub-task in terms of efficient actions or which agent(s) should work on it is specified in our model. Besides, in the Bayesian inference experiment, the code could give accurate action prediction with enough database, and also avoid some time consuming because the blank time between subtasks is saved.
Citrus Yellow Shoot Disease Detection based on YOLOV5
Authors: Wang Shenglong , Zhang Yixin , Li Runqi
Published: April 2023

Citrus yellow shoot disease (also called Huanglongbing in Chinese) is a devastating disease of citrus. A large number of experiments have shown that citrus yellow branch disease cannot be cured, but can only be prevented and controlled. Traditional detection methods are limited by long time and low coverage, and cannot predict diseases in time. Thanks to the powerful feature representation capabilities of convolutional neural networks, the detection of citrus yellow shoot disease based on deep learning has become the mainstream of current research. In this paper, we transform the recognition task of citrus greening disease into the detection of lesion area, focus on the feasibility of using deep learning association algorithm to identify the symptoms of citrus yellow shoot disease, and evaluate the recognition accuracy. Specifically, we preprocessed the collected citrus plant images to construct the training data set, and built a citrus yellow shoot disease recognition model based on the YOLOv5s algorithm. The results show that the accuracy reaches 91.3% and the recall rate reaches 88.9% after detection by YOLOv5s model. Finally, it is found that this model can accurately find citrus products with citrus yellow shoot disease, so as to timely prevention and control, improve the identification efficiency of citrus yellow shoot disease and reduce the cost of detection.
Enhanced Knowledge Distillation via Parameter Re-definition
Authors: Wang Ziquan , Zhao Yulin , Cheng Lidong
Published: April 2023

Due to the high scalability of deep learning and its ability to manipulate large-scale hyperparameters, it has achieved great success in many fields. However, encoding such a large-scale data set is ultimately at the cost of expensive computing power and storage resources, which has also prompted model compression and model acceleration to become a hot topic in recent years. Model pruning, weight decomposition, reduction of model accuracy, weight sharing, etc. are all currently popular solutions, but they have a common problem that they cannot ensure that the compressed model is as good as the original model, and they are all based on the original model. to modify. This paper draws on the method based on knowledge distillation, introduces the concept of Renyi-divergence popularized by KL-divergence, and proposes a loss function that has been based on Renyi-divergence distance metric, and uses the rigor of the student network as a hyperparameter. A student network model that minimizes the loss function under rigor. We validated our results on ResNets using the cifar-10, cifar-100, and imagenet datasets. It improved the basic model by 0.6%, and the absolute gain of Top-l accuracy exceeded 1.6%.
Regression-based Analysis of Ozone Layer via Machine Learning Models
Authors: Dong Yiran
Published: April 2023

Ozone protects the livings on the earth from ultraviolet radiation. The emission of ozone depleting substance causes the Antarctic ozone hole and reduces the ultraviolet radiation absorption rate by ozone layer. Researchers find that ozone depleting substances (ODS) accounts for ozone concentration between 9 km and 25km, by chemical-climate models and ozone concentration will increase by 15% until 2050. In this work, we used six major ODS consumption worldwide and mean stratospheric ozone concentration each year. Seven regression models are implemented to make prediction and k-fold cross validation is used for avoiding overfitting. Root mean squared error (RMSE), and standard deviation are two performance metrics of regression models. The results indicate that the prediction from support vector regression achieved the lowest RMSE. Random forester and k-nearest neighbor are also appropriate for make prediction. We also concluded that linear, polynomial, ridge, and lasso regression methods are hardly to fit the data in this application.
Analysis Effect of Bias lying in Artificial Intelligence: A Survey
Authors: Liu Bangdao , Wang Keyao , Yang Mutian
Published: April 2023

Bias, which is one of the most significant social problems, can be reflected the Artificial intelligence. Those biases can be classified into three categories: Gender bias that shows the divergence between males and females, the religious bias that favors some beliefs over others, and racial bias that can be embodied in different AI’s utilization efficiency by whites and nonwhites.
Based on the Difference Equation of Forest Ecological and Economic Optimization Management Solution
Authors: Sun Yujie , Liang Guangxin , Zhang Zhijian , Huang Qianqian , Yuan Haoshu , Feng He
Published: April 2023

Forests lay emphasis on meeting ecological balance, carbon sequestration, social mate-rial needs, and promoting economic development. The paper will explore an integrated forest management and utilization model to maximize the benefits in all aspects of forest. To find the factors that affecting forest carbon sequestration, the grey correlation method was used to analyze the age structure and annual precipitation. Then the key index, age structure, which is affecting forest carbon sequestration was obtained. For qualitative and quantitative research on forest carbon sequestration of the trend of change over time, Saihanba was selected as the research object, then ArcGIS visualization analysis was conducted. Furthermore, polynomial function was utilized in Matlab data fitting toolbox to fit the data, then a logistics regression model in line with the situation of forest carbon sequestration was obtained. According to this model, we developed the integrated forest management model based on difference equation. This model can facilitate the finding of an optimal cutting intensity coefficient K to obtain the optimal forest management scheme. It also paves the road in getting the relationship between forest carbon sequestration with time.
Computer Engineering Research: Innovative Treatment Methods and Genetic Analysis of Digestive Tract Diseases based on Neuroscience and VR Technology
Authors: Qin Yi , Li Ting , Liu Zhenyu , Zhang Yan , Luo Jun , Huang Xushuang , Li Liangyu
Published: April 2023

Background: According to the data from the Autonomous University of Barcelona, Spain, at present, 20% of people in the world may suffer from irritable bowel syndrome. Research methods: The research group has carried out computational engineering modeling for music therapy of irritable bowel syndrome, which uses virtual reality technology that can interfere with human biological neural network, and has also carried out the process design of biological neural network working mechanism, using computer engineering to complete necessary stimulation, and using neural network algorithm model to complete in-depth learning, After the algorithm modeling is successful, it can complete the prediction of the improvement of patients by music chords of different emotional colors, and provide clinicians with new ideas for treatment and health economic intelligent products. The first author looks forward to the cooperation between Chifeng University and Barcelona Autonomous University in the research of irritable bowel syndrome, expounds the advantages of both sides, and expresses a strong willingness to communicate. At the same time, the advantages of the Sakharov Institute in Belarus are discussed. Results: The research team carried out research in combination with biological neural network experiment and social experiment, and completed the market demand survey. Conclusion: The chord trend in this model can complete the intervention for patients. Patients have better subjective feelings, and the algorithm model is highly popularized. Virtual reality technology can be used as an important medium to complete this work, which is suitable for promotion.
Analysis of the composition of ancient glass objects based on cluster analysis and random forest methods
Authors: Chen Zhiying , Shang Dongchen
Published: April 2023

In ancient times fluxes were often added to the production of glass to lower the melting point of pure quartz sand. During the smelting process, the addition of different products resulted in significant changes in the internal composition of the glass products. This paper examines a sample of ancient glassworks, based on the data from several sources. The data are divided into 'weathered' and 'unweathered', and cluster analysis reveals significant differences between the categories, and random forest analysis is used to determine the non-linear relationship between the variables, resulting in a chemical composition correlation of the relationships were more variable for potassium chloride and lead chloride and smoother for the rest. This paper innovatively adopts a combination of K-means cluster analysis and random forest to evaluate the composition and identification problems of ancient glass objects. The model in this paper can also be extended to other studies related to the degree of weathering in ancient wooden shipwrecks, metals, ceramics, and other aspects.
Application and Challenges of Statistical Methods in Biological Genetics
Authors: Sun Jingyi
Published: April 2023

Humans are curious about genes, from plants to animals, from breeding to diseases. For centuries, it has been considered a genetic disease. With the development of medicine, people have also realized that many diseases are heritable. With the birth of modern statistics, humans have created many models. This article focuses on the application of statistical methods in biological genetics. This paper introduces the principles and their applications of Least Absolute Shrinkage and Selection Operator Regression, the Chen-Stein Method, and Logical Regression model in different branches, such as gene set selection. These models can effectively tackle the problem of reproducibility in genetics to a certain extent when used correctly. In addition, they offer an effective means of data analysis in genetics field. Although the three models have their weaknesses, such as the use and selection of a priori, it is reasonable to believe that with the continuous improvement of the models by mathematicians, they can have better prospects.
Study on the preparation of C4 olefins by ethanol coupling based on multiple regression analysis
Authors: Xu Yizhou , Liu Jianxun , Zhou Rui
Published: April 2023

With the continuous development of the current chemical industry, the demand for olefins as raw materials for the production of chemical products and pharmaceutical intermediates is increasing. Compared with traditional fossil energy, ethanol is an excellent green raw material for the production of C4 olefins. In the preparation process, the selectivity of C4 olefins and the conversion rate of ethanol depend to a certain extent on the reaction temperature and the catalyst of the reaction, so the reasonable selection of catalyst and temperature becomes very important. In order to study the effects of different catalyst combinations and temperatures on ethanol conversion and C4 olefin selectivity, a multiple regression model was established and its endogeneity was tested by Monte Carlo simulation. The stepwise regression method was used to select the appropriate independent variables, and then the model was optimized to reduce the dimension, and the first optimized linear regression equation was obtained. Finally, in order to test and eliminate the heteroscedasticity of the model, this paper uses the combination of White test and Wls least squares estimation and robust variance error to obtain the second optimized linear regression equation.
Glass classification and identification based on logistic regression model and K-means clustering analysis
Authors: Ji Zijie
Published: April 2023

In order to investigate the effect of chemical composition on weathering, all post-weathering data were transformed into pre-weathering, for which the basis for the classification of high potassium and lead-barium glasses was inferred using a support vector machine algorithm. Afterwards, a detailed subclass differentiation method was determined for the two main classes of glass based on the K-means cluster analysis method. Further classification is then carried out on the basis of what is known about the classification. To identify unknown glasses, logistic regression was also carried out on the composition of weathered samples to predict the pre-weathering content.
Exposure Pathways and Toxicity of Fullerenes
Authors: Liu Botao
Published: April 2023

Fullerenes have become very popular nowadays in the field of cosmetic and medicine as “radical sponge” because of their high antioxidant activities. However, there are worries about the toxicity of fullerenes due to their special chemical properties and good ability to enter the human body. In this article, it is found that fullerenes have been proved to have the ability to enter animal body through skin penetration, peroral administration and pulmonary absorption beside initiative injection. The potential mechanism of fullerene toxicity is to interrupt the activation process of protein, cause mitochondrial dysfunction and generate ROS to damage organism. Nevertheless, the experiments result shows the negative effects of fullerenes only occur in a high dose and the assessments of fullerenes toxicity show a low result with the IC50 value and LD50 value to be 383.4 lg/mL to HEK293 and 721mg/kg to mice. It is suggested that fullerenes can rarely affect human health as long as people are exposed to the appropriate dose of fullerenes and the toxicity of fullerenes can further reduce via synthesis of fullerene derivates.
A new method for the composition analysis and classification of ancient glass products before and after weathering
Authors: Zhao Jiayi , Tang Ziyang , Deng Jianyue
Published: April 2023

This paper focuses on the composition analysis of ancient glass artifacts. With the help of chemical composition data from different locations of glass artifacts, the chemical compositions of weathered and unweathered points are compared using the chi-square test as well as the visualization of R. We find that the chemical compositions of SiO2 and K2O have significant changes before and after weathering. Then the composition of weathered points before unweathering was predicted by using the feature point ratio method and neural network prediction. Further, with the help of tools such as Python, modeling methods such as support vector machine and random forest classification were used to dichotomize high potassium and lead-barium glass and compared with the actual results. Then, by using principal component analysis, clustering heat map, and K-means clustering, the composition-based subclassification of glass was established, and the rationality of the subclassification and classification model was verified with the literature, and finally, the sensitivity and rationality of the classification method was analyzed with the defined sensitivity function. The work of this paper will hopefully contribute to the archaeological identification of the composition of glass products.
Lead toxicity
Authors: Yang Dengnan
Published: April 2023

Lead is a heavy metal. It is frequently used in life as a result of its distinct physical and chemical features. It is, nonetheless, a hazardous and widespread heavy metal. Lead is not only a common occupational and environmental toxin, but it also has a significant effect on children's brain development. Additionally, despite the fact that studies on the biochemical and molecular mechanisms underlying lead's harmful effects are still lacking, some research suggests that there may be indirect mechanisms at play. By examining lead's effects on various human body parts and therapeutic strategies for lead poisoning, this essay highlights the pathogenic factors and responses of lead on human tissues. As a result of lead's ability to quickly cross the blood-brain barrier and the growing brain's immature endothelial cells, the data demonstrate that lead is particularly detrimental to the central nervous system. The creation of synaptic connections and neuronal migration are significantly influenced by the normal growth of glial cells. Glial cells may prematurely differentiate as a result of lead exposure, impairing their ability to communicate with neurons. Lead appears to have genotoxic effects not just directly but also indirectly through free radical generation or DNA repair inhibition. The current study provides useful information for future toxicological research on lead poisoning.
Research Progress on the Application of Biomass-Based Porous Carbon Materials in Lithium Battery Electrode
Authors: Ruan Jianjin , Xie Yifan , Ye Zhiyu
Published: April 2023

With the growth of the world population, limited non-renewable energy sources, oil and coal mine are becoming increasingly exhausted. The long-term consumption of fossil energy not only causes an energy crisis, but also makes ecological and environmental problems more significant. Therefore, lithium batteries, as an energy storage tool, have been studied by a number of researchers due to their advantages such as high specific energy, little environmental pollution and long cycle life. For secondary batteries, the performance of electrode materials affects the development of batteries. Biomass-derived porous carbon materials have the advantages of cheap, easy-to-obtain from raw materials, large specific surface area, many pore structures, strong electrical conductivity, adjustable pore structure, and have been widely concerned in recent years and used as electrode materials for energy storage lithium batteries application. In the process of charging and discharging lithium batteries, porous carbon materials can provide more space for lithium ions to be embedded and removed from the electrode, improving the capacity and thus the efficiency of the battery. In this paper, the main preparation technology of biomass-derived carbon materials and the improvement technology of heteroatom doping are reviewed. The application effects of different activation methods on the porous carbon materials prepared by plant materials in the negative electrode of lithium battery are compared, and the performance of the materials in practical application is evaluated in the paper, which provides reference materials for the beginners of using biomass structure to prepare porous carbon materials.
Research Progress of Environmental Risk Substances in the Preparation of Biochar
Authors: Xu Mengdie
Published: April 2023

Biochar is a kind of solid material containing high carbon, which is obtained from biomass such as agricultural and forestry wastes through photosynthesis in oxygen free or low oxygen environment and pyrolysis at high temperature. It has many advantages, such as wide source of raw materials, high specific surface area, developed pores, and high stability. With the wide application and promotion of biochar in various fields, some hazardous substances to the environment generated in its preparation process, such as heavy metals and metalloids, polycyclic aromatic hydrocarbons, persistent free radicals, soluble organics and metal cyanide, should also be focused on and studied. In this paper, three types of environmental risk substances (i.e. heavy metals, polycyclic aromatic hydrocarbons and persistent free radicals) are studied, and their harm to the environment and ecological are explored, as well as the prospects for future development. Through careful selection of raw materials and the optimization of preparation conditions, the toxicity and harm can be suppressed to some extent.
Application of Biostatistical Models in Public Health under Mpox Virus
Authors: Li Jiahe
Published: April 2023

Since January 1, 2022 last year, many countries outside Africa have begun to have outbreaks of Monkeypox (Mpox) virus. The first case of Mpox transfusion was confirmed on 16 September 2022 Chinese mainland. In order to prevent major public health events, the aim of this study is to predict which populations in China are more susceptible to Mpox virus infection. There are two main research methods used in this paper: literature research method and statistical analysis method. The proportion of male cases in different groups was mainly analyzed separately, and the proportion of the data was determined by a 95% confidence interval. Second, analyze the true proportions of these factors through demographic information. Semen samples and rectal swabs of the type from the confirmed case are then transmitted to determine how Mpox virus is transmitted. Finally, sex-age (proportion hospitalized) was counted. The results of the experiment are: the proportion of male cases is the highest, and the true proportion of male sex and sexual transmission ratio of the influencing factors is the highest. The main types of transmission are: sexual contact, other, and between people. Men in the 18-49 age group and women in the 18-59 age range had the greatest hospitalization rates, respectively. The conclusion is that men who have sex with men, sex actors, HIV-positive patients, women aged 18-59 and men aged 18-49 are the main target groups in China and are susceptible to Mpox virus.
Progress in the Application of Genetic Engineering in Life Detection
Authors: Wang Ziyuan
Published: April 2023

Since December 2019, the outbreak of SARS-CoV-2 has become a major public health challenge, which has a significant impact on the life, health and production of people around the world. Aflatoxin and kanamycin, which can enter the human body through food, and fluoride, which is widely present in the daily environment, are strong carcinogens. Therefore, the detection with high sensitivity, low detection limit and simple operation is needed for those pathogenic bacteria and compounds that endanger human health in life. However, the traditional laboratory operation has some defects, such as the need for expensive instruments, cumbersome operation and a certain demand for professionals. The rapid development of genetic engineering provides an excellent opportunity for the innovation of detection methods. In this paper, the contribution of genetic engineering in detection is briefly reviewed.
Component Analysis and Identification of Ancient Glass Products Based on Correlation Analysis
Authors: Li Shirui
Published: April 2023

The Silk Road was an important channel for cultural exchanges between ancient China and the West, and glass was a precious material evidence of early trade exchanges. In order to explore the changes of relevant properties and chemical compositions of these glass relics before and after weathering, it is necessary to calculate their correlation degree and predict the changes of compositions. In this paper, the correlation and correlation between the components are calculated by establishing the grey correlation analysis method, independent sample T test method, random forest algorithm, K-means algorithm and other models, so as to analyze and predict the correlation properties and chemical components of glass relics before and after weathering.first, preprocess the data, remove the invalid data, and take the glass type, decoration and color as the comparison sequence. Whether the cultural relic surface is differentiated into a reference sequence, use the gray correlation analysis method to calculate that the gray correlation between the glass type and whether it is differentiated is the largest, which is 0.7939, indicating that the glass type is most closely related to whether it is weathered. According to the type of glass, the average, median and standard deviation are calculated, and the chemical composition with strong correlation with weathering is determined by independent sample t-test. The prediction results are obtained by predicting the principal components of weathering points.
Research Methods of Carbon Emissions
Authors: Dong Qianxiao
Published: April 2023

As a pillar industry, the construction industry generates 28% of the total carbon emissions of the whole society throughout its life cycle. Through the carbon emission ratio of the whole life cycle of existing buildings, it is found that the carbon emission per unit time in the construction phase is the highest among all phases, and the various environmental pollution caused by it is also the most concentrated. In order to achieve low carbon construction and reduce environmental pollution, relevant parts of the country have promulgated building construction management documents since 2007. The documents put forward clear requirements for green and low-carbon urban and rural construction to ensure green and low-carbon construction activities. It can be seen that in the context of the "two carbon" strategy, carbon emission monitoring and carbon emission reduction of construction have attracted wide attention from all walks of life. In this paper, through the analysis of carbon emission monitoring methods of construction projects, a carbon emission calculation model based on carbon sources and sinks of the construction process is established to realize the quantitative calculation of carbon emission in the construction phase of construction projects. It also establishes a carbon emission monitoring method for the construction phase of the construction project, which provides practical guidance for the carbon emission data monitoring of each construction project and guides the real-time monitoring of carbon emission during the construction phase of the construction project.
Composition analysis and identification of ancient glass products
Authors: Sun Wenyu , Wang Xiaoyi
Published: April 2023

Based on the proportion of various components of ancient glass products and the classification method, the composition, change and relation of different types of cultural relics under different weathering conditions are analyzed in detail in this paper. The statistical rules and the basis for the classification of cultural relics are given, and on this basis, the unknown types of glass cultural relics are identified. Firstly, a statistical model is established, and Chi-square test is used to analyze the factors that affect the weathering of cultural relics. It is concluded that the weathering of cultural relics is related to the type of glass and the type of decoration, and the type of glass has a greater influence on the weathering. The chemical composition of the weathered cultural relics before weathering is predicted. Then, after the classification rule of glass is preliminarily explored, the grey correlation model is established to calculate the correlation degree between each chemical component and the two kinds of glass, and then the K-means clustering model is used to divide the glass into subclasses. Thirdly, BP neural network was used to analyze the chemical composition of glass relics of unknown category, identify their types, and analyze the sensitivity of classification results. Finally, according to the idea of discrete Frechet distance algorithm, the cultural relics are grouped according to the type of glass, and the discrete Frechet distance of the broken line of the change rate of the content of different chemical components between cultural relics is used as the basis to judge the correlation relationship, and the correlation relationship between the two substances is analyzed.
Composition analysis and identification of ancient glass products
Authors: Wang Minghao , Cui Ruochen , Xue Yulong
Published: April 2023

Ancient glass chemical composition is diverse, and because of the environmental impact of weathering, the proportion of its composition will change, affecting the judgment of the glass category. Therefore, according to the relevant data, this paper queries a large number of literature, through reasonable statistical analysis to find the classification basis, and studies all kinds of glass relics before and after weathering, in order to play an important role in the composition analysis and identification of ancient glass products.To define the standard of correlation, so as to better explain the correlation degree of the respective chemical composition of the two types of glass; then, to compare the difference between the two types of glass in the above correlation relationship. The comparison model of individual differences was then established, and the gap between the two individual correlation coefficient was calculated from the absolute value distance, and compared with the defined evaluation criteria, which concluded that the glass of the two categories had significant individual differences in each pair of content of chemical composition. For example, both potassium oxide and calcium oxide are chemical components, with the absolute value distance of 1.319, and the difference level is very significant.
"Internet + Standardization" University Waste Classification Market-oriented Operation Alliance Investigation and Research
Authors: Li Shoucai , Wang Lihao , Chen Fan , Qu Kaiyue
Published: April 2023

With the advent of the Internet era and the improvement of people's living standards, more and more garbage is generated per capita. If backward countries can realize garbage recycling, they can turn waste into treasure, which can not only reduce environmental pollution but also avoid resources of waste. The "Internet + Standardization" university garbage classification market-oriented operation alliance came into being. It uses the "Internet" as a technical means, based on standardized garbage classification, and uses a new market mechanism in various colleges and universities to encourage college students to take the initiative to classify garbage and improve college students. Environmental awareness. During the implementation process, we will establish an integrated platform that benefits schools, students, merchants and recycling enterprises, form a market-oriented mechanism of multi-subject linkage of resource recycling and reuse, improve the environmental protection awareness of college students, and explore a road for garbage classification suitable for implementation in China.
The use of college students' suitcases and experimental design
Authors: Yang Yijia
Published: April 2023

Although the technology is gradually developing, and the suitcase is gradually developing towards intelligence and convenience, which has become an indispensable existence for carrying out work, there are still many problems in the use of the suitcase. In order to grasp the future development trend of suitcases, understand the shortcomings of suitcases at this stage, and meet the needs of some people, I conducted a questionnaire survey on 18 college students and invited them to participate in the experiment. According to the volunteers' responses in the questionnaire, "stair handling" is the most difficult scenario for using suitcases. Design the experiment based on this data, and invite volunteers to participate in the experimental design, record the most commonly used ways of volunteers when carrying stairs, and analyze the final statistical results.
Discover two Neural Machine Translation model variables' effects on Chatbot's performance
Authors: Wang Youwei
Published: April 2023

To offer automatic online advice and help, chatbots are sophisticated conversational computer systems that resemble a human conversation. As chatbots' advantages grew, a variety of sectors began to use them extensively to give customers virtual support. Chatbots take advantage of methods and algorithms from two Artificial Intelligence areas: Machine Learning and Natural Language Processing. There are still several obstacles and restrictions to their use. In order to discover two NMT model variables' effects on chatbot performance, this paper does several experiments on a deep neural network chatbot model. Two straightforward and useful kinds of attentional mechanisms are used in this chatbot model: a local technique that only considers a small subset of source words at a time, as opposed to a global approach that always pays attention to all source words. This paper conducts experiments to examine how different model variables affect chatbot performance. This paper created a question template with eight general questions to test chatbot performance. Through the whole experiment results, increasing the number of iterations and increasing the dataset scale can improve the vocabulary and logic of the chatbot dialog to achieve better performance.
Mechanism and Optimizations of Aqueous Zinc-ion Battery
Authors: Mo Ziyu
Published: April 2023

Nowadays, more and more problems of environmental deterioration make the development of environmentally friendly energy imminent. For the requirements of low cost, high security, and high efficiency, aqueous Zn-ion batteries are a promising trend for research. In this paper, the mechanism of aqueous Zn-ion batteries will be illustrated in three aspects: cathode materials, zinc anode, and electrolytes. Moreover, possible alternatives for each part of the batteries will be comprehensively illustrated in detail. In addition, the challenges such as short capacity, zinc dendrites, and corrosion and passivation will be analyzed and the possible corresponding solutions will be proposed. Finally, a concise conclusion will be given.
The design the Simulation of Smart Pet Home
Authors: Liu Kejun , Wen Haoran , Wu Zhaojun
Published: April 2023

More and more families have their pets and pets become an essential part of our daily life. This article is to solve the problems of temperature and humidity control, automatic weighing, and automatic opening of cage door. The simulation of the design demonstrate that the new design is more accurate and automatic including the DHT11, AT89S52, DT711, LCD1602. All these hardware consist the whole system, especially AT89S52 is the most paramount part of the design which is the microprocessor while the LCD screen as the output device. The DHT11 and DT711 works as input device which would collect the data of temperature and humidity, also the weight. If the sensors sample the abnormal data and send to the microprocessor, then the microprocessor would send the order of the alarm and the adjustment module which contain the fan, heater, humidifier.
Social robot navigation in environments with different population density
Authors: Yao Jialu
Published: April 2023

In the field of modern robotics, robots need not only to avoid obstacles, but also to meet the comfort of pedestrians. In this paper, two methods of robot navigation: CP-SFM and reinforcement learning are introduced. CP-SFM model can analyse the repulsive force between the pedestrians and robot and generate a pedestrian-friendly path to the destination. Reinforcement learning method create a crowd-human interaction and use deep learning framework to train the robot learning human-robot and human-human interaction. These methods are also applied to the simulation environment and the results show the success of them.
Comparative Analysis the Super-Resolution Image Generation Performance Based on BigGAN and VQ-VAE-2
Authors: Cai Lingtao
Published: April 2023

Super-resolution image reconstruction has always been a popular research direction in the field of computer vision, which aims to recover high-resolution clear images from low-resolution images. Traditional super-resolution reconstruction algorithms mainly rely on the construction of constraints and the accuracy of registration between images to achieve the reconstruction effect, but their accuracy cannot meet the needs of practical applications with large multiples. Thanks to the rapid development of deep learning field, super-resolution image reconstruction based on deep learning has become the mainstream, and has achieved great success in reconstruction accuracy and speed. According to the different generative models used, the existing super-resolution image reconstruction methods mainly include two categories: GAN-based and VAEs-based. To quantitatively compare the limits of the two approaches' performance, this study selects two representative algorithms, BigGAN and VQ-VAE-2, and introduces the theoretical details and training process of these two methods, respectively. Furthermore, the reconstruction results of BigGAN and VQ-VAE-2 are further compared. Finally, this paper discusses the future development trend of super-resolution picture reconstruction with the current potential problems of BigGAN and VQ-VAE-2.
Analysis of Wordle Game Mechanism Based on LSTM and MLP
Authors: Zhou Yixi , Cao Hanyang , Jia Xuanbo
Published: April 2023

This paper uses data analysis, deep learning and natural language processing techniques to study the difficulty and result distribution of word guessing based on the Wordle game mechanism. First, a three-layer LSTM model is established to predict the number of reported results, and the correlation between word factors and guessing difficulty is analyzed. Next, a multi-sequence LSTM model combined with NLP models is established to predict the result distribution of specific words at specific times. Finally, an MLP classification model is built to classify the difficulty of words.
A Study on the Identification of Glass Artefacts Based on Multiple Logistic Regression
Authors: Han Yujie
Published: April 2023

In this paper, traditional glass artefacts are classified into four categories, and the common factors obtained from factor analysis are used to solve a multivariate logistic regression model to avoid the 'pseudo-regression' caused by multiple covariance, and then predict the unknown types of glass artefacts. The BP neural network structure was also constructed based on the data, and the optimal solution was obtained after 1000 iterations using Bayesian regularization to minimize the sum of squares of the errors, provided that 10 neurons were used. The glass samples were identified to belong to the categories of unweathered high potassium, weathered lead barium, unweathered lead barium, unweathered lead barium, weathered lead barium, weathered high potassium, weathered high potassium and unweathered lead barium.
Research on the Design Problem of Maximum Wave Energy Output Power
Authors: Yang Chaoyi , Yang Zihan , Ji Wentao , Lu Yan
Published: April 2023

With the development of economy, energy and environment problems have become a big problem in today's society. To realize sustainable development and protect ecological environment has become the consensus of all countries in the world. Wave energy, as an important Marine renewable resource, is more widely distributed than conventional energy, with abundant energy storage and considerable application value. In this paper, based on the analysis of the heave and pitch motion of the wave energy device in seawater, the motion states of the float and vibrator from static to heave and pitch motion are obtained through the force analysis of the float and vibrator and the establishment of differential equations. The maximum output power of the wave energy device is analyzed and discussed by adjusting the damping coefficient of the damper and other related parameters.
Machine Learning and Multiple Regression-Based Study of the Medicinal Properties of Food
Authors: Zhou Jiasheng , Fan Zhihong , Zhang Wenxin
Published: April 2023

We study the relationship between food ingredients and hot and cold properties based on the idea that "medicine and food have the same origin". Firstly, we classify foods with known hot and cold properties as typical representatives of flat, warm and cold properties, and use various machine learning algorithms to classify the typical food representatives. In order to further improve the reliability and accuracy of the classification, we applied Bayesian optimization to the SVM and the SVM was able to classify the typical food representatives again with an accuracy of 96.53%. Based on the above findings, we further analysed which chemical components played a key role in the hot and cold properties. We then applied multivariate logistic regression for quantitative analysis, using stepwise forward regression to minimise complete multicollinearity and OLS + robust standard errors to eliminate the effect of heteroscedasticity. Based on the analysis of the coefficients of the regression equations and the significance test results, the conclusions reached were consistent with the qualitative analysis, with the four main components of energy, water, minerals and fat playing a major role in the chilling and heating properties of food. In conjunction with the analysis in the full text, we make recommendations for the development of functional foods where heat and cold are the principles.
NÂNG CAO NHẬN THỨC CỦA SINH VIÊN VỀ VĂN HÓA TRUNG QUỐC – TRƯỜNG HỢP SƯỜN XÁM
Authors: Đỗ Tiến Quân , Dương  , Hoàng
Published: April 2023

Văn hóa trang phục người Trung Quốc là một chủ đề quan trọng đối với những sinh viên Việt Nam chuyên ngành ngôn ngữ Trung Quốc. Dưới góc độ ngôn ngữ học so sánh, trên cơ sở lý luận khoa học và thực tiễn, bằng phương pháp điều tra, khảo sát, thống kê, so sánh, phân tích và tổng hợp, bài viết làm rõ nhận thức của sinh viên chuyên ngành ngôn ngữ Trung Quốc, Trường Đại học Hùng Vương về Sườn xám truyền thống của người Trung Quốc trong sự so sánh với Áo dài Việt Nam, đặt cơ sở khoa học cho những giải pháp, kiến nghị về việc dạy và học tiếng Hán tại Việt Nam dưới góc độ người dạy.