bluuebunny/crossref_metadata_2025 huggingface dataset:
Construction Method of Casino based on Ethereum
Authors: Rong Jianzhi
Published: April 2023

There are a lot of things that humans cannot do, and one of them is being fair, especially when he is running a casino. However, Ethereum can. Constructing a casino that is regulated by Ethereum can give us the first fair casino in the world. With the help of some technics of cryptography, which are public/secret key schemes and one-way functions, the secrecy and privacy in the gambling of each player can be ensured while still making the game fair by the blockchain. During the construction, Ethereum is also found to be fit for the casino’s other aspects such as propaganda and payment. By successfully constructing such a casino, a way of converting the fixity of blockchain into fairness is proposed in the area that needs it and lacks it the most, which is a casino. Following down this road, any area that lacks fairness can exploit Ethereum or block-chain to find a way to achieve fairness.
The Analysis of the Risks and Improvements of ERC20 Tokens
Authors: Zhang Changjin
Published: April 2023

Blockchain is a decentralized, shared ledger that aggregates blocks of data in a factual data structure in chronological order using a chain structure. Two hundred sixty thousand tokens, or 98% of the around 2.5 million smart contracts in Ethereum network, are ERC-20 tokens. The ERC20 standard specifies constructors for token contracts that establish and initialize the contract state. The Ethereum wallet and Ethereum decentralized, centralized applications can access tokens through these standard interfaces. Security vulnerabilities in ERC-20 have drawn a lot of attention lately in recent years. This paper summarizes some basic security vulnerabilities and suggests avoiding multiple withdrawal attacks. Tokens can be used to support dApps, access blockchain services, trade, and obtain voting rights. Various tokens exist depending on their properties and use cases, including governance, utility, security, transaction, and platform tokens. Tokens can be sorted as fungible tokens and non-fungible tokens. Tokens that can be fungible are identical, divisible, and can be instead of money. Non-fungible tokens have a single owner and are unique.
Difference between ECDSA with ED25519 and Their Future
Authors: Luo Yiming
Published: April 2023

It is always a trendy topic about virtual currency nowadays in the world. These virtual currencies like Bitcoin and Monero are precious and cryptic, which play a more critical role in the economy since no departments or governments control their transactions and deals. How could the transaction system provide users with security and protect their property? What's more, one of the most important characteristics is that all the transactions are untraceable, which means that the governments and the users cannot figure out the identity of another user. This paper discusses some principles of Bitcoin and Monero. For instance, some encryption algorithms like ECDSA and ED25519 are applied to help users to verify the whole transaction, and Ring signature is used in Monero to conceal the user's identity. Meanwhile, this article will also compare some encryption algorithms' security and efficiency. Moreover, there would be a discussion about some advanced communication technologies. For example, there would be a brief introduction to quantum communication and entanglement. Then, it would also have an intense debate about the future of ECDSA and ED25519 if quantum communication and quantum entanglement were invented.
Improving the Performance of Deep Q-learning in Games Pong and Ms. Pacman
Authors: Wu Kaiyuan , Xu Ningzhi
Published: April 2023

Unlike TD-gammon architecture, deep Q-learning algorithm combines deep learning and reinforcement learning, and it has achieved outstanding results in many Atari games. This study primarily focuses on two games, Pong and Ms. Pacman. It explores several approaches to improve the performance of deep Q-network (DQN). Based on the data obtained, while DQN displays a high-level performance in the simple Atari game Pong, it struggles a bit when learning the more complex game Ms. Pacman, leading to diverged loss. This under-performance may be partly explained by the shorter training time than the original paper due to limited computational resource. Given sufficient time of training and exploring, the model is believed to eventually converge once it identifies the optimal combination of hyperparameters.
Research of the Methods on Multi-Agent Path Finding
Authors: Zhou Ruining
Published: April 2023

Multi-Agent Path Finding is an essential real-life application of multi-intelligent systems for which scholars have solved many classical solutions. And with the evolution of theories related to machine learning, intelligent solutions are emerging daily. However, these algorithms have not been well summarized and concluded, and are comparatively difficult to consult. This essay's objective is to offer a thorough analysis of these issues. The paper will start with Path Finding and describe its three categories of classical algorithms. And then it will focus on the centralized planning algorithms based on the classical algorithms, and the distributed execution algorithms based on machine learning, and provide a theoretical explanation and comparison of their effectiveness. Finally, a prospection and outlook on the currently unresolved issues in the Multi-Agent Path Finding research area, including unification standards and directions for improvement, will be presented.
Comparative Analysis of Reinforcement Learning Algorithm based on Tennis Environment
Authors: Bai Yu , Dong Haoyu , Lian Qiwei
Published: April 2023

Reinforcement learning and deep reinforcement learning, as a research hotspot in the field of machine learning, have been widely used in our daily life. In this field, game is playing an extremely important role in the developing of reinforcement learning algorithms. Based on the Tennis environment built by Unity ML Agents, this paper used three algorithms, Proximal Policy Optimization (PPO), Multi-Agent Deep Deterministic Policy Gradients (MADDPG) and Soft Actor-Critic (SAC), combined with PyTorch framework, solved the continuous control problem of this environment. Meanwhile, a group of optimal parameters are obtained through multiple trainings, so that Agents can achieve a perfect effect of solving the continuous control problem in Tennis environment. At the end, this paper compared and analyzed the difference among these three algorithms, summarized the application and properties of each algorithm. For different parameters of the algorithm, this paper also maked a comparison and explained the reasons for some special cases as well which can be used for the future work.
Image Denoising based on Deep Learning
Authors: Li Zeyu
Published: April 2023

Image denoising has always been one of the research hotspots in the field of image processing, which aims to remove the noise from the imaging device or external noise environment and other interfering factors in the image to restore the noisy image to the original clean and noise-free image. Mature algorithms and machine learning techniques have been developed previously for different application situations and specific computer vision works. Image denoising based on deep learning can adaptively learn image content and is suitable for image denoising tasks in high-noise environments. This paper builds a model based on the representative image denoising algorithm DnCNN, and discusses the performance difference with other denoising algorithms. All the results show the new methods are usually more efficient than traditional ones which can process pictures that are under more complex conditions.
Studies Advanced in Image Style Transfer based on Deep Learning
Authors: Shen Yifei , Tang Guo , Xu Qiaoyu
Published: April 2023

Image style transfer (IST) is a hot topic in the computer vision community, which refers to learning the distribution of a given style image to convert any image into corresponding image style while the content of the original image is preserved as much as possible. Early style transfer mainly utilizes texture features. Thanks to the great improvement of deep learning technology, researches on IST based on convolutional neural networks (CNN) have achieved breakthroughs in accuracy and speed. Focusing on the topic of deep learning-based IST, we will introduce the latest algorithms in detail, including their basic ideas, key steps, advantages, and disadvantages. Also, we will give an analysis of the performance of representative methods. Furthermore, we discuss the problems to be solved in style transfer and summarize the challenges and development trends in the future.
Artificial Intelligence: The Significance of Tesla Bot
Authors: Su Yihao
Published: April 2023

The rising humanoid robot industry has brought significant interest from the public and treasure seekers who see this industry as the future. Tesla, a leading motor manufacturer and artificial intelligence company, has also joined the competition of humanoid robots by introducing “Optimus.” The service robotics industry, which “Optimus” focuses on, is fast-growing, with approximately 119% growth over the last four years. Compared with its competitors, Tesla has a few advantages. First of all, it has abundant experience in the field as it has accumulated countless data on human behavior through the beta that its Tesla cars have provided over the years. In addition, Tesla has more capital than its competitors. As of September 10th, 2021, Tesla has a market capital of 939 billion dollars. However, Tesla is also known for its overconfidence in its products, as it usually exaggerates the delivery date and the capability of its products. Another obstacle that Tesla faces comes from the industry itself. Admittedly, it is not a mature industry without much experience that Tesla can learn from. As a result, like many of its competitors, Tesla has to develop all of its technologies in-house, leading to the high prices of humanoid robots on the market. However, suppose Tesla is able to develop a complete version of “Optimus” faster and better than its competitors. In that case, it is very likely for Tesla to become the leader in the humanoid robot industry.
Casualty on the Titanic based on Machine Learning Methods
Authors: Liu Yang
Published: April 2023

The Titanic sank on April 15, 1914, with 2224 people on board, and only 32% survived. The survivors are somewhat random, but they are somewhat the same. Studying the types of people who are more likely to survive in a disaster will promote an understanding of the values and ideology of the society at the time. Therefore, this study collected data on some of the passengers on the Titanic and the survivors through Kaggle. This study predicts the survival of passengers through data cleaning, feature engineering, dimensionality reduction processing, and different models such as Random Forest, Decision Tree, KNN, and Logistic regression. In this study, it was found that Age, gender, representation of socioeconomic status, and whether they traveled alone were associated with survival rates. Among them, the decision tree and random forest models scored 98.65, which performed the best and had the highest prediction accuracy. After visualizing the data, this study concluded that survival rates were higher for females, children younger than ten years old first-class passengers, and non-solitary travelers.
Deficiencies and Upgrades in Artificial Intelligence Languages
Authors: Li Ruoxuan
Published: April 2023

In the era of artificial intelligence, people have started to have a lot of exposure to machine output language, such as online translation robot customer service, Siri, Microsoft Ice. However, these AI languages are still in the primary stage. Compared with human languages, AI languages still have many shortcomings, for example, lack of intentionality, lack of metaphorical ability. And people need to make some changes and improvements to make them reach a higher level of intelligence, so that AI languages can be closer to natural languages in various aspects, and AI products can better facilitate human production and life, as well as better serve society. This article is written around AI language, through the existing products of AI language as an example, analyzing AI language from different levels such as linguistics and philosophy, finding out the deficiencies of AI language and the aspects that need to be improved, and finally putting forward constructive opinions on how to make today's AI language reach a higher level of intelligence, that is, paying attention to the importance of metaphor in AI, and people should solve the problem of In order to solve the problem of "intelligence", the problem of "intelligence" needed to be solved first; people should not only deal with the problem of man and the world but also deal with the problem of man, nature and the imaginary world.
Deep Learning Network Traffic Prediction based on Bayesian Algorithm Optimization
Authors: Lv Yuantao
Published: April 2023

In order to solve the problem of low prediction accuracy caused by artificial determination of hyperparameters of network traffic prediction model, this paper applies Bayesian optimization algorithm (BOA) to the determination of hyperparameters of neural network, and proposes a CNN-LSTM network traffic prediction model based on Bayesian optimization algorithm. The local features and long-term development trends of the data are mined by combining the Convolutional Neural Network (CNN) and the Long Short-Term Memory Neural Network (LSTM), and the Bayesian optimization algorithm is used to calibrate the hyperparameters. This paper uses real network traffic data to test and compare with LSTM, GRU and other models. Experimental results demonstrate that the proposed BOA-CNN-LSTM model reduces the RMSE and MAE by 21.17% and 27.52%, compared to the traditional network traffic prediction model. The results presented in this paper show that the Bayesian optimization algorithm can more quickly and accurately calibrate the hyperparameters of the model, which provides a new method for predicting network traffic time series data in the future.
Analysis and Identification of the Composition of Ancient Glass Objects based on Statistical Research and Machine Learning Algorithms
Authors: Sun Caoyuan , Li Zewen
Published: April 2023

In order to promote the study of ancient glass artifacts, this paper integrates the weathering principle and the nature of chemical elements in glass, and analyzes the color and chemical composition of glass using statistical and machine learning methods. First, the classification and regression tree featuring Gini index is applied to explore the classification criteria of high potassium glass and lead barium glass, and the accuracy of the model is tested by 10-fold cross-validation. Secondly, subclasses were classified for the collected sample data. In this paper, Two Step Cluster Algorithm is used to divide the high potassium glass into four subclasses and the lead barium glass into five subclasses based on the Euclidean distance between the samples. Finally, the Spearman’s rank correlation coefficients between chemical components are computed separately based on the proportion of each chemical component in glass to explore the correlation between them.
Classification and prediction of the chemical composition of glass based on grey and principal component Logistic regression
Authors: Zhang Hanyi , Luo Yuwen , Chen Yang
Published: April 2023

As a momentous witness of the ancient Silk Road trade, glass’s variety identification and measurement or even prediction of its chemical constituent content are significantly important for people to have a systematic understanding of it. However, glass weathering tends to occur because of the ambient conditions of the place where it is buried, which may bring some difficulties to the classification and content prediction. Based on the data provided in problem C of the National Undergraduate Mathematical Modeling Contest in 2022, the GM (1,1) grey prediction model has first constructed so that the content ranges of various pivotal components are achieved. Then several glass samples whose category is unknown could be classified based on a principal component logistic regression model of the chemical composition’s content.
The Potential Health Issues of Nanoscale Additives in Food Industry
Authors: Lu Ziqi
Published: April 2023

Nanotechnology is widely used in medicine, electronics and food industries. Among them, in the food industry, nanotechnology is mainly used in the fields of food packaging and food additives. Many foods now contain food additives, and nanotechnology has become an important part of it. However, it is not known whether these nanoparticles are actually beneficial to the environment and the body. There is proof that they also negatively impact human health by looking up and examining online scientific papers and experimental data. This paper introduces metal particles like silver and gold nanoparticles used as food additives which protects food and applies coloring, Moreover, inorganic substances with nutritional benefits like titanium dioxide and zinc oxide were utilized as food dyes, then discusses the nanoscale additives’ negative effects on human body like toxicity or cell death, following the damage to human body for instances gut and liver damage, DNA and cell damage, inflammation of the liver, kidney and spleen.
Composition Analysis and Identification of Ancient Glass Products Based on Optimized BP_Adaboost Strong Classifier
Authors: Tan Yaodi , Jing Zhiyuye , Yang Gaofei
Published: April 2023

Due to the different combustion agents used in the manufacture of glass in ancient China and abroad, there are apparent differences in the composition of ancient glass products in China and abroad. This paper presents a reduction analysis and identification of the composition of ancient glass products, which is of great significance to the study of the Silk Road and the history of the development of glass products. This paper analyzes and identifies the composition of ancient glass products based on the data of C questions of the CUMCM competition. The study first used a neural network optimized by a genetic algorithm to screen out the elements closely related to the weathering condition and used  regression to reduce the composition of the weathered samples. The reduced samples were subclassified by systematic clustering according to their respective compositions, and high-potassium glass and lead-barium glass were classified into two subclasses each. The classification basis was reasonably clarified by factor analysis. Finally, the  strong classifier was optimized to identify and classify the samples based on the unknown sample components. The correct identification rate reached 100%, which played a good role in distinguishing the weathered Chinese and foreign glass products.
Research on Glass Classification and Recognition based on Support Vector Machines
Authors: Guo Shimeng , Gan Jinwei
Published: April 2023

Glass artefacts undergo weathering and a significant exchange of internal elements due to burial in the ground. In order to classify the glass types, Principal Component Analysis was used to transform the existing chemical indicators into a small number of principal components. Subsequently, Support Vector Machine approach was used to classify the glass types to be predicted based on the selected principal components. K-means clustering algorithm was then used to classify the two glass types into subclasses on the basis of the selected chemical components and to perform sensitivity analysis. Using this model, the glass types of the samples to be tested can be identified.
A study of ancient glass based on a modeling perspective
Authors: Wang Xiaohan , Li Jingwen , Dai Lingong
Published: April 2023

As a valuable physical evidence of the cultural exchange between China and the West in ancient times, ancient glass is of great research significance. However, ancient glass is highly susceptible to weathering by the burial environment, and previous studies have only applied statistical methods for simple classification and generalization. In order to further study the composition analysis and prediction of ancient glass, glass subclass classification and identification, this paper constructs a data prediction model based on the theory of chi-square test, decision tree classification, and BP neural network prediction, so that the research on ancient glass can broaden the current research progress from a new perspective.
The Toxicity of Bisphenol A and Its Analogues on Human
Authors: Gong Wenjun , Wei Xuan Yu
Published: April 2023

With the development of human society, technology and medicine have been widely discovered. Bisphenol A (BPA) is a kind of substance widely used in industrial production, mainly used in the production of polycarbonate, epoxy resin and other polymer materials. Many analogues of BPA like BPS, BPF and BPAF have been used as substitutes for BPA. However, BPA and its analogues exposure in daily life has been found to be harmful to people's health. In this paper, the toxicity of BPA and its analogues in the environment exposed with different concentrations, exposure time, ages, genders has been discussed. In addition, the effects of BPA and its analogues on biological endocrine system, immune system, reproductive system and nervous system have been introduced by studying the endocrine organs of animal models. Results reveal that DNA can be severely damaged at certain BPA concentration, and that BPA may act directly on the ovary due to its similar structure to secreted estrogen Besides, BPA exerts a bi-directional regulatory effect on the mouse immune system, and when exposed to BPA for a long time, activity of immune system can be suppressed. Researches on BPA and its analogues’ effects on organs and systems can give some suggestion on the use as materials for the production.
Gold Nanoparticle Based High Throughput Screening
Authors: Xu Shizheng
Published: April 2023

In the COVID-19 pandemic that began in January 2019, antigen detection has made an immeasurable contribution to the pre-detection of the virus. Conjugates with gold nanoparticles (Au NPs) are distinguished. At the same time, nucleic acid detection is widely used in the accurate detection of a large number of samples, and it is a high-throughput detection method. HTS technology is a feature of future and present bio-detecting, which can make targets more easily and accurately detected, while Au NPs could be gained without too much cost and help build high throughput characterization, as well as enabling pre-detection. Thus, the combination of both HTS technology and Au NPs are widely expected and researched for their future potential. This article reviews the detection method combined with gold nanoparticles and high-throughput technology, which makes the detection more efficient, can carry a larger sample base, and has a high degree of accuracy. By researching on building HTS and making use of Au NPs, the detecting technology can be fully improved and can help fasten the progress being made in pharmaceutical industry, thus creating a promising method for preventing epidemic.
Classifying the chemical content of cultural relics using the decision tree CART classification model
Authors: Wang Zihan
Published: April 2023

In this investigation, the decision tree CART classification model was used to obtain the decisive relationship between various chemical components on glass type, and Matlab was used to calculate the classification criteria of the decisive chemical components, to make a decision tree diagram to determine the glass type, and to summarise the distribution law of barium oxide, silica and alumina content to determine the glass type. The most determining 8 chemical components were then selected based on the Fisher score expression in the feature selection model, which calculated lead oxide, potassium oxide and other components as classification criteria.
Composition analysis and identification of ancient glass products
Authors: Wang Wenyang , Chen Yunpeng , Gu Xinyu
Published: April 2023

Aiming at the problem of composition analysis and identification of ancient glass products, a multiple linear regression model based on least square method was established, and the relationship between surface weathering and type, ornamentation and color was obtained.Firstly, the data were preprocessed, and the invalid data were eliminated by BP neural network, and the basic information of glass relics was quantified.Secondly, a multiple linear regression model was established, and the least square method was used to obtain that the surface weathering was negatively correlated with ornamentation, and positively correlated with color and type.Secondly, a component correlation model based on Spearman's coefficient was established to analyze the statistical rules of chemical components.Finally, JB test was used to verify whether the components obey the normal distribution, and the normal distribution test was completed.
A Technical Comparison of YOLO-Based Chest Cancer Diagnosis Methods
Authors: Shi Juanlang
Published: April 2023

Cancers have become one of the deadliest diseases in the world, and early diagnosis becomes vital for a patient's survival. As deep learning advances, YOLO has become an attractive tool as it supports real-time interactions. Thus, YOLO is expected to be applied in cancer diagnosis. A technical study of a YOLO-based computer aid diagnosis system for chest cancers is presented in the paper. Four kinds of the image in cancer diagnosis, histopathological images, mammograms, CTs, and Low-dose CTs, are introduced. Three issues of implementing a computer aid diagnosis system (CAD) are discussed and analyzed, including the usage of handcrafted features, the high false positive rate in clinical practice, and difficulty in detecting irregular nodules in spiral CTs. In discussion, the drawback of handcrafted features in the region of interest (ROI) extraction can be addressed by applying extra architectures like ResNet50 as extractors. A trained network can serve as a non-nodule filter to reduce the false positive rate in diagnosis. Image data can be categorized based on morphological features in data preprocessing to train a more sensitive model, then irregular-shape nodules can be detected by CAD.
Facial expression classification
Authors: Ren Zhuoyue
Published: April 2023

At present, emotion classification has become a hot topic in artificial intelligence pattern recognition. The facial expression recognition (FER) is indispensable for computers to understand the emotional information conveyed by expressions. In the past, using traditional features to extract and classify facial expressions has not achieved satisfactory accuracy, so the classification of facial emotions is still a challenge. The model used in the paper is an existing one - MINI_XCEPTION, the dominant framework for CNNs that extracts features from images to identify and classify seven facial emotions. The model was trained on a dataset of people’s facial expressions (Kaggle). This model has a significant improvement over the previous model.
Facial Expression Recognition with ViT Considering All Tokens towards More Informative Self-attention Outputs
Authors: Song Haorui
Published: April 2023

Currently few works have been done to apply Vision Transformer (ViT) on facial expression recognition (FER) successfully. In this paper, we put forward a novel idea of processing the outputs from the multi-head attention in ViT by passing through a global average pooling layer, and accordingly design 2 network architectures, namely ViTTL and ViTEH. These 2 models, especially the latter one, show more strength in recognition of local patterns, which normal ideas hold that it is a weakness of ViT. Extensive experiments are conducted on the benchmark dataset FER-2013 with popular state-of-the-art models employed as baselines for comparison. The results demonstrate the superiority of the 2 new models in the realm of FER.
Object Removing via Multi-Column Gate Convolutional Neutral Network
Authors: Huang Haipeng , Yuan Haikun
Published: April 2023

Object removal is to remove unwanted objects in a photograph. It can be realized by the inpainting technique with irregular mask. Generative Image Inpainting with Contextual Attention [n] and Partial convolution cannot work well with irregular mask，so we present a Multi-column Gate Convolutional Neutral Network. It can work well with both regular and irregular mask. Our model adopts gate convolution which is more suitable in inpainting task than traditional convolution. Special context loss, semantics loss and spatial reconstruction loss are used for better performance. We train the model with CelebA and Landscape. A comparison is made between our model and some models published on CVPR etc, our model’s results can generate more realistic images than existing ones for object removal.
Ethereum: Introduction, Expectation, and Implementation
Authors: Huang Qichen
Published: April 2023

As the Blockchain technology develops, more and more cryptocurrencies were invented after Bitcoin. This paper introduces the technology of Blockchain, including the basic concept of Blockchain and how Blockchain works to allow decentralization of trades; The system of Ethereum and the cryptocurrency Ether (ETH), how it was invented, what was the central mission of its invention, as well as how it differs from Bitcoin and how can it allow more decentralized application to be developed, which in turn illustrates what it means and where its values lie. As all cryptocurrency markets have a huge fall in value in the year 2022, as shown in figure 1, many people are losing faith in cryptocurrency. Many believe that since it is entirely digital and non-government based, it has no actual value, that the entire cryptocurrency market is a bubble. Meanwhile, cryptocurrencies introduce a very revolutionary concept, which is the decentralization of applications, and this decentralization can apply to many things, leading to a great technological structure modification, even for social structures. Because of its anonymous and democratic nature, there is also always going to be demand for cryptocurrencies. Thus, this paper also analyzes the expectations of cryptocurrency, mainly Ether, and the predictions of its future development.
Fashion Outfit Recommendation and Transformation Using Generative Adversarial Network Methods
Authors: Meng Xinyi
Published: April 2023

Over the last few decades, generative adversarial network (GAN) methods have been increasingly applied and improved in fashion-related scenes, especially during the pandemic. This article provides an overview of several mainstream GAN models for fashion recommendation and fashion transformation, including compatibility matrix-regularized GAN, Outfit GAN, transformer-based GAN, conditional analogy GAN, disentangled cycle-consistency try-on network, and flow-navigated warping GAN. Within each GAN method, the improvements made to perform more related and deliciated are presented with detailed loss functions, the specific evaluation matrixes, and the examinations of generators or discriminators. Moreover, possible directions of improvements for future research and problems with existing models are involved. As for the common restrictions of included methods, including the problem of incomprehensive and non-diverse datasets, the standard evaluation of modish aesthetic value, and the number of fashion items involved in one outfit, are analyzed within fashion outfit recommendation and fashion transformation. Therefore, such restrictions provide possible directions for future analysis in fashion-related networks.
Composition Analysis and Category Prediction Model of Ancient Glass Based on Decision Tree
Authors: Chen Jieyin
Published: April 2023

Ancient glass is easily affected by environmental factors, which cause chemical changes between glass composition and environmental substances and leads to weathering. It is important to analyze the chemical composition of ancient glass for the study of the Silk Road. To study the composition of glass cultural relics, the relationship between surface weathering and glass type, ornamentation and colour was analyzed first, and then qualitative analysis was carried out through a frequency distribution map, and grouping was carried out according to glass type and surface weathering type, the statistical distribution law of each chemical composition was studied, and the loss of chemical composition with or without weathering was analyzed; Finally, the chemical composition content of the weathered sample before weathering is predicted according to the chemical composition ratio of the weathered and non-weathered cultural relics. The experimental results show that the model has good robustness and can be used to prepare and quickly predict the composition and classification of ancient glasses.
Research on the Recommendation of Exercise Recovery Duration of Mobile Health APP
Authors: Yin Yue , Dong Yuxin , Li Jiale , Li Sixuan
Published: April 2023

With the further deepening of people's demand for health, the use of mobile health apps has become more popular. The recovery duration suggestion function of the mobile health App can provide more scientific exercise guidance and good exercise experience, but there are still some shortcomings, such as low data utilization, and the suggestion is difficult to be accurate to individuals. In this paper, questionnaire survey is used to collect data, and a hidden Markov prediction model based on K-means clustering analysis is established. Through training the collected data, a more scientific analysis of the recovery time after exercise can be finally given. Finally, we give some suggestions on the future development of sports bracelets.
Identification of Ancient Glass Components Based on Grey Correlation Analysis
Authors: Guo Ziqian , Wang Xiaohuan , Hu Yaoyi
Published: April 2023

The article is based on mathematical modelling of the significant data of the two categorize glass specimen to examine the factors influencing the climate of the covering of the glass artefacts, to derive statistical patterns and correlations of the chemical composition content, on this basis, the subclasses are classified, and the accurate categorization manner applied to the analysis and discovery of glass composition is given. On the basis of data processing, the association between weathering of glass surface and glass kind, adornment and color is analyzed by using visual histogram. And it was found that the weathering of lead-barium glass was more serious than that of high-potassium glass, that B-grain decoration was easily weathered, and that black and light blue glass were the most severely weathered. The most significant effect on weathering is due to the content of silica in the lead-barium group, and the most significant effect on weathering is due to the content of sodium oxide in the high-potassium group. The correlations between the 14 chemical components in the two categories of high potassium glass and lead-barium glass were analysed by establishing a grey correlation analysis model, and the correlations between the different chemical components in the different categories were calculated and ranked. Similarly, the correlation between lead oxide and magnesium oxide was the highest in the high potassium group, while strontium oxide, tin oxide and sulphur dioxide were all less correlated, i.e. the correlation between this component and other chemical components was characterised by the ANOVA.
SỰ ĐA DẠNG CỦA CÁC BIỂU ĐẠT VĂN HÓA TRONG ĐỜI SỐNG ĐỒNG BÀO DÂN TỘC THIỂU SỐ Ở VIỆT NAM TRONG BỐI CẢNH HỘI NHẬP VÀ PHÁT TRIỂN
Authors: Trần Quốc Hùng , Phương Đoàn
Published: April 2023

Văn hóa là lĩnh vực mang tính phổ biến nhất trong các lĩnh vực của đời sống xã hội. Bởi văn hóa hiện hữu trong bất kỳ không gian, thời gian nào, trong mỗi quốc gia, lãnh thổ, dân tộc, tôn giáo hay trong từng thực hành văn hóa của mỗi người. Nhờ sự phổ biến đó, mà văn hóa trở lên đa dạng thông qua sáng tạo, thực hành và trao truyền văn hóa.
PHÁT TRIỂN VĂN HÓA ĐỌC TRONG KỶ NGUYÊN SỐ
Authors: Vũ Thị Thanh Minh , Huyền
Published: April 2023

Văn hóa đọc có ý nghĩa lịch sử sâu sắc, đánh dấu các mốc phát triển của xã hội loài người và mang đậm dấu ấn lịch sử qua các thời kỳ. Từ những tri thức tích lũy được thông qua việc đọc, văn hóa đọc sẽ tạo điều kiện, nền tảng để phát triển tâm hồn, trí tuệ, nhân cách cho mỗi cá nhân. Trong kỷ nguyên số, văn hóa đọc với những phương thức đọc mới càng khẳng định rõ tầm quan trọng đối với sự phát triển của mỗi cá nhân cũng như của cộng đồng và xã hội. Bài viết phân tích thực trạng văn hóa đọc ở nước ta, trên cơ sở đó đề xuất một số giải pháp nhằm phát triển văn hóa đọc trong kỷ nguyên số ở Việt Nam nói chung và trong các trường đại học nói riêng là rất cần thiết trong giai đoạn hiện nay.
SỰ VẬN DỤNG PHÉP BIỆN CHỨNG DUY VẬT CỦA CHỦ TỊCH HỒ CHÍ MINH VÀO SỰ NGHIỆP CÁCH MẠNG VIỆT NAM
Authors: Phạm Thị Kiên
Published: April 2023

Trước những biến đổi sâu sắc của thời đại và yêu cầu phát triển đất nước, tư tưởng biện chứng duy vật được Chủ tịch Hồ Chí Minh vận dụng tài tình và sáng tạo là bài học đối với Đảng và nhân dân ta trong công cuộc xây dựng, bảo vệ và phát triển đất nước trong thời đại mới theo định hướng xã hội chủ nghĩa trên nhiều lĩnh vực, như: phát huy nội lực kết hợp chủ động với hội nhập quốc tế; xây dựng đội ngũ cán bộ có đức có tài; xây dựng đạo đức mới, văn hóa mới; xây dựng Đảng và Nhà nước thật sự trong sạch, vững mạnh,... đem lại chìa khóa cho sự tiến bộ và phát triển bền vững trong nhận thức và hoạt động thực tiễn. Do đó, bài viết làm rõ phương pháp biện chứng duy vật được Hồ Chí Minh vận dụng như là một sợi chỉ đỏ xuyên suốt sự nghiệp cách mạng của dân tộc Việt Nam.
HỌC THUYẾT HÌNH THÁI KINH TẾ - XÃ HỘI VÀ Ý NGHĨA CỦA NÓ ĐỐI VỚI SỰ PHÁT TRIỂN CỦA VIỆT NAM HIỆN NAY
Authors: Bùi Xuân Dũng
Published: April 2023

Việc nắm vững học thuyết hình thái kinh tế - xã hội của C.Mác là cơ sở để xây dựng và phát triển đất nước theo hình thái kinh tế - xã hội chủ nghĩa xã hội. Muốn vậy, trong thời kỳ quá độ đi lên chủ nghĩa xã hội Việt Nam cần đẩy mạnh phát triển nền kinh tế thị trường định hướng xã hội chủ nghĩa, chuyển đổi cơ cấu sản xuất theo hướng đẩy mạnh công nghiệp hóa, hiện đại hóa và chủ động, tích cực tăng cường hợp tác, mở rộng hội nhập quốc tế.
PRESIDENT HO CHI MINH’S PEOPLE’S IDEOLOGY AND IMPLICATIONS FOR CIVIL ADVOCACY IN HO CHI MINH CITY TODAY
Authors: Trần Hải Hà
Published: April 2023

The article researches President Ho Chi Minh's views on civil advocacy. The results showed that President Ho Chi Minh raised the guiding views on civil advocacy work such as the concept, position, role, force, method and process of implementing civil advocacy work. These views have so far remained valuable to the Party's civil advocacy. The article also points out the significance of President Ho Chi Minh's civil advocacy thought for civil advocacy in Ho Chi Minh City today.
NÂNG CAO CHẤT LƯỢNG DẠY HỌC TIẾNG ANH CHUYÊN NGÀNH QUẢN LÝ CỬA KHẨU CHO HỌC VIÊN ĐÀO TẠO ĐẠI HỌC TẠI HỌC VIỆN BIÊN PHÒNG
Authors: Nguyễn Thúy Hằng
Published: April 2023

Việc giảng dạy tiếng Anh cũng như tiếng Anh chuyên ngành quản lý cửa khẩu đang được Đảng ủy, Ban Giám đốc Học viện Biên phòng (Bộ Tư lệnh Bộ đội Biên phòng) đặc biệt quan tâm. Nhận thức rõ được tầm quan trọng của môn học đối với công tác quản lý và bảo vệ biên giới, công tác đối ngoại của Bộ đội Biên phòng, Bộ môn Ngoại ngữ - Khoa Khoa học Cơ bản Học viện Biên phòng, thời gian gần đây đã chủ động đổi mới phương pháp giảng dạy, lên kế hoạch đề xuất đi khảo sát thực tế tại đơn vị cơ sở, ghi lại hình ảnh tại thực địa, xây dựng các bài giảng mang tính trực quan sinh động, giúp người học sử dụng ngôn ngữ tiếng Anh trong công việc một cách hiệu quả nhất.
RESEARCH ON THE SELECTION OF FAST STRENGTH DEVELOPMENT EXERCISES FOR MALE HANDBALL ATHLETES AT DANANG UNIVERSITY OF PHYSICAL EDUCATION AND SPORTS
Authors: Kiều Trung Kiên
Published: April 2023

Through the use of observation methods, discussion interviews, pedagogical testing methods and statistical methods, the article has selected 26 exercises, including 10 group exercises, 11 coordinated exercises and 5 game exercises – a competition to develop strength. At the same time, the article also selected 5 tests to assess the speed of male handball athletes at Danang University of Physical Education and Sports.
DẠY ĐỌC HIỂU TIẾNG VIỆT CHO HỌC VIÊN QUỐC TẾ TẠI HỌC VIỆN CẢNH SÁT NHÂN DÂN
Authors: Nguyễn Thu Thủy , Phương
Published: April 2023

Đọc hiểu là một hoạt động chiếm tỷ lệ khá lớn trong quá trình dạy và học một ngoại ngữ cũng như trong các hoạt động học tập và nghiên cứu khác. Đối với học viên quốc tế học tập tại Học viện Cảnh sát nhân dân, đọc hiểu là nhân tố mang tính quyết định để thiết lập một kênh cung cấp kiến thức nền về ngôn ngữ, văn hoá, đất nước, con người và kiến thức chuyên ngành cảnh sát một cách hiệu quả nhất. Vì vậy, mục tiêu của dạy đọc hiểu là nhằm củng cố và mở rộng kiến thức, kỹ năng ngôn ngữ của học viên thêm một bước nhằm chuẩn bị cho họ bước vào giai đoạn học tập các môn học của chương trình đào tạo sỹ quan cảnh sát. Thông qua các hoạt động đọc hiểu, người dạy có thể cung cấp cho học viên vốn ngữ liệu tiếng Việt cảnh sát một cách trực tiếp, tập trung nhất và chính xác nhất. Với phương pháp phân tích, tổng hợp những tài liệu thứ cấp và xuất phát từ thực tế giảng dạy tiếng Việt cho học viên quốc tế tại Học viện Cảnh sát nhân dân, bài viết đề xuất các giải pháp nhằm nâng cao khả năng đọc hiểu cho học viên quốc tế khi học tiếng Việt.
Çocukluk Dönemi Korkuları ve Bir Müdahale Aracı Olarak Sanal Gerçeklik Uygulamasının Kullanımı
Authors: DÖNMEZ Ayşegül , TÜRK Aytuğ
Published: April 2023

Korku insanoğlunun bebeklikten yetişkinliğe değin uzanan gelişim dönemlerinin her birisinde görülmekte ve şiddetli düzeyde psikolojik uyaran ile ilişkili olarak ortaya çıkan bir duygudur

Henüz yeni doğmuş bir bebeğin ses gibi dış ortam kaynaklı bir uyaran karşısında ağlaması ya da çırpınma şeklinde fiziksel tepkilerde bulunması dış dünyayı tanıma sürecindeki bebeğin yaşamış olduğu korku duygusunun ilk göstergelerinden birisi olarak kabul edilebilir. Ne yazık ki ülkemizde korku, çocuklar üzerinde denetim sağlamak amaçlı sık sık başvurulan bir yöntemdir. Yetişkinlerin çocuklar üzerinde bir yaptırım ya da ceza yöntemi olarak uyguladıkları çocuğun karanlıkla tehdit edilmesi ya da karanlık bir odaya kilitlemesi gibi davranışlar çocukların karanlığa karşı korku duygusu geliştirmesine neden olmaktadır. Çocukluk döneminde yaşanan bu korkular o kadar engelleyici ve bozucu bir hale gelebilir ki, bu durum bazen çocuğun özgül fobi tanısı kriterlerini karşılamasına yol açabilir. Bu nedenle erken çocukluk döneminde yaşanan korkulara yönelik uygun yaklaşım müdahalelerinin, sonraki dönemde yaşanması olası problemlerin önüne geçilmesi açısından önemli olduğu düşünülmektedir. Uygun müdahale yaklaşımlarının başında da günümüz gelişen teknolojisi ve imkanları doğrultusunda sanal gerçeklik tabanlı uygulamaları gelmektedir. Bu derlemede de çocukluk dönemi korkuları ve bir müdahale aracı olarak sanal gerçeklik uygulamalarının kullanımı değerlendirilecektir.
Öğrenci Hemşirelerin Siber Zorbalık Durumlarının ve Etkileyen Faktörlerin İncelenmesi
Authors: TOPCU Ege Miray , UĞURYOL Merve , ÖZGÜR Gönül , POLAT Eda
Published: April 2023

Amaç: Araştırma hemşirelik öğrencilerinde siber zorbalık ve etkileyen faktörlerin incelenmesi amacıyla yapılmıştır.

Gereç ve Yöntem: Tanımlayıcı desende planlanan araştırma 2018-2019 öğretim yılında İzmir ilinde yer alan bir hemşirelik fakültesinde öğrenim görmekte olan 292 öğrenciyle yürütülmüştür. Veriler “Tanıtıcı Bilgi Formu” ve “Siber Zorbalık Ölçeği” ile toplanmıştır. Araştırmadan elde edilen verilerin analizinde, “Mann Whitney U Testi”, “Spearman Korelasyonu” ve “Kruskal Wallis Testi” kullanılmıştır.

Bulgular: Öğrencilerin SZÖ toplam puanlarının ortalaması 27.10±7.64 dür. Öğrencilerin siber zorbalık durumu düşük bulunmuştur. Araştırma bulguları öğrencilerin SZÖ puan ortalaması ile cinsiyet, internet kullanım süresi, internet kullanım davranışları ve algılanan okul başarısı arasında anlamlı bir ilişki olduğu bulunmuştur.

Sonuç: Araştırmada hemşirelik öğrencileri arasında siber zorbalığın görüldüğü, siber zorbalık davranışlarında cinsiyetin ve internet kullanımının öncelikle dikkate alınması gereken etkili faktörler olduğu sonucuna varılmıştır.
RISCO, PERSONALIDADE E ENDIVIDAMENTO: UM ESTUDO COM UNIVERSITÁRIOS DE BAIXA RENDA
Authors: De Assis Fabio Rangel , Gomes Sabrina Kaylane Cardoso , Silva Paulo Vitor Jordão da Gama
Published: April 2023

Os aspectos psicológicos do comportamento humano tiveram uma nova perspectiva em diversos campos. A personalidade, desde então, não era vista como uma simples descrição do indivíduo e sim associada as decisões do cotidiano. Este trabalho busca entender como a tomada de risco pode sofrer influência da personalidade e das atitudes frente ao endividamento dos jovens universitários de baixa renda da baixada fluminense do Rio de Janeiro. Foram desenvolvidas regressões múltiplas com a variável independente sendo a tolerância ao risco (Grable & Lytton, 1999) e as independentes os traços de personalidade (Hernandez, 2009; Goldberg, 1992), atitudes frente ao endividamento (Moura, 2005) e as características sociodemográficas. Os principais achados em relação a tomada de risco apontaram uma associação positiva e significativa do traço de personalidade masculino, bem como a estabilidade emocional, a extroversão e das atitudes frente ao endividamento. Foi possível notar que nas situações de vulnerabilidade financeira as mulheres podem assumir papeis de protagonismo em suas famílias, sendo mais estáveis emocionalmente e possuindo traços mais característicos do masculino.
ANÁLISE DO GRUPO DE “QUADRILHA FEIJÃO QUEIMADO” NA PERSPECTIVA DO LAZER SÉRIO
Authors: Ferreira Higor de Queiroz , Silva Sérgio Tadeu Junio Alves , De Oliveira Saulo Neves , Apolinário-Souza Tércio , Maciel Marcos Gonçalves
Published: April 2023

A dança em grupo conhecida como quadrilha junina é uma atividade folclórica muito popular entre os brasileiros. No entanto, pouco se sabe sobre o que as experiências desenvolvidas nessa atividade representam para os seus praticantes, especificamente aos que pertencem a grupos que se dedicam a participar em campeonatos. Assim, o presente trabalho tem como objetivo analisar a participação dos membros do grupo da “Quadrilha Feijão Queimado”, partir das qualidades distintivas do lazer sério. Para a coleta de dados utilizamos a versão brasileira do Serious Leisure Inventory and Measure (SLIM).  Participaram da pesquisa 20 integrantes do referido grupo (10 pessoas de cada sexo), com idade entre 15 e 29 anos (25 ±4,5 anos). Os resultados apontam para a presença das qualidades do lazer sério, como também sugerem que a participação no grupo promove o desenvolvimento de algumas dimensões específicas adotadas por esse construto, tais como a autorrealização, expressão de habilidade e prazer. Concluímos que a participação no grupo de “Quadrilha Feijão Queimado” pode ser caracterizada como um lazer sério, assim como contribui para o desenvolvimento de sentimentos de identidade, pertencimento, reconhecimento.
METAVERSO: UM OLHAR SOB A PERSPECTIVA DA EDUCAÇÃO
Authors: Da Silva Mônia Lorena do Nascimento , Bastos Mairiane Ferreira , Da Cunha Thaynara Ribeiro
Published: April 2023

O trabalho em questão busca abordar um tipo de mundo virtual específico: o metaverso e a forma com que o uso de ferramentas tecnológicas tem sido inserido na educação, bem como suas características positivas e negativas. Trata-se de uma temática ainda pouco abordada no âmbito educacional, entretanto, de suma relevância, tendo em vista a dinamização que o usa das tecnologias e ferramentas digitais têm trazido para as salas de aula. Para realização da pesquisa, utilizou-se a pesquisa bibliográfica como metodologia.