bluuebunny/crossref_metadata_2025 huggingface dataset:
Based on Cluster analysis model for glass classification problem
Authors: Liu Chenxi , Wu Zekai , Dong Xin
Published: April 2023

The research on the chemical composition and other physical properties of ancient glass is a very important aspect of ancient glass research, which can provide scientific evidence for archaeological research and help to study the composition system, manufacturing age, preparation process and technical origin of ancient glass. Based on the cluster analysis model, this paper establishes a suitable classification model, which provides a correct classification judgment for weathered glass affected by the external environment. The specific work is to classify the rules of glass products, classify each category, and analyze the rationality and sensitivity.
Composition Analysis of Glass Based on Weighted Mean and Correlation Analysis
Authors: Shao Kaiyue , Du Ruifang , Xiong Hangyu
Published: April 2023

Due to weathering and other external influences, the surface and chemical composition of ancient cultural relics will be corroded to a certain extent. This paper analyzes the chemical composition of two main kinds of ancient glass, high potassium glass and lead barium glass, classifies the cultural relic samples according to the type and weathering degree, and studies the chemical composition content rule of weathered samples respectively through descriptive statistics. The weighted average was used to predict the chemical constituents before weathering, and the correlation analysis of the main constituents was carried out. The composition analysis of ancient cultural relics in this paper lays a foundation for further effective measures to protect and restore cultural relics.
Analysis of economic growth forecast based on regression model
Authors: Chen Ziyuan
Published: April 2023

In this paper, the population growth retardation model, the unitary linear regression model and the multiple linear regression model are established to solve the problem. After considering the year and population relationship, the total population and the future labor population are predicted by the growth retardation model, and the future education investment and the investment in fixed assets of the whole society are predicted by the unitary linear regression model. After considering such factors as education investment, total population, labor force population, and investment in fixed assets of the whole society, establish a linear relationship between the economy and these factors, and then solve the change of GDP under the joint influence of these factors through multiple regression analysis, and then predict that the economic growth rate in the next 20 years will be 4.71%, 4.49%, 4.29%, 4.10%, 3.93%, 3.78%, 3.64%, 3.51% 3.39%, 3.28%, 3.18%, 3.08%, 2.99% 2.91%, 2.83%, 2.75%, 2.68%, 2.61%, 2.55%, 2.48%. It can be seen that the future economic growth rate shows a downward trend. The growth rate of GDP per capita in the next 20 years will be 4.26%, 4.05%, 3.86%, 3.69%, 3.54%, 3.40%, 3.27%, 3.15%, 3.05%, 2.95%, 2.86%, 2.77%, 2.69%, 2.62%, 2.54%, 2.48%, 2.42%, 2.36%, 2.30%, 2.25%, showing a decreasing trend. Finally, it is concluded that the average annual growth rate of GDP per capita in the next 20 years will be 7%.
Perceived Organizational Support and Psychological Contract of the Editors and Proofreaders of P Press
Authors: Zhang Yuanman , Erorita Siegfried M.
Published: April 2023

Employees' perceived organizational support can increase their psychological contract with the organization to a certain extent, which can motivate them to perform, so that they are willing to contribute to the organization's goals. As a result, the organization and employees can work together to create a better work environment. This paper examines the perceived organizational support and psychological contract of editors and proofreaders at P Press and provides a reference for human resource management at P Press in terms of providing organizational support to employees and establishing a psychological contract between employees and the organization.
Analysis of chemical composition of ancient glass products based on grey correlation method
Authors: Bian Siyu
Published: April 2023

The Silk Road was the channel of cultural exchange between China and the West in ancient times, and the glass is the precious material evidence of early trade. Early glass was often made into bead-shaped ornaments and introduced into our country in West Asia and Egypt. After absorbing the technology, the ancient glass in our country was made locally. Although the appearance of the glass products was similar to the foreign ones, the chemical composition was different. Therefore, the analysis and identification of chemical composition is an important aspect to identify and study ancient glass products. In view of the different contents of weathering or non-weathering chemical components of different types of glass relics, this paper considers the types, patterns, colors, chemical components and other factors, and ignores environment-related factors, such as atmospheric environment, pH value, burial time, depth and other factors. Based on the existing data and relevant research results of domestic and foreign scholars, the classification rules of chemical components of high-potassium glass and lead-barium glass were obtained by using grey correlation analysis model, Chi-square test and improved weighted average algorithm. It is pointed out that the contents of , , and should be observed in order to analyze and identify ancient glass products.
Research on glass classification and identification based on heritage samples
Authors: Liu Zhiyuan
Published: April 2023

The study of ancient glass has been intensified in archaeological circles today, but its susceptibility to weathering can affect archaeologists' ability to classify it. In order to classify glass artefacts, this paper establishes a 'subclass classification model based on the sum of the absolute values of relative changes' and uses the K-means clustering algorithm to classify the subclasses. In order to identify different classes of glass objects, the chemical composition of the glass is extracted from the centroids of the different subclasses, and the Euclidean distance between the class centres is solved for, and the class represented by the class centre with the lowest Euclidean distance is taken as the class corresponding to the unknown object.
Research on Glass Classification and Recognition Based on Fisher's Linear Discriminant and Hierarchical Clustering
Authors: Rong Tengyuan , Liang Yu
Published: April 2023

Buried in the ground, the glass cultural relics weathered, and a large number of internal elements were exchanged. In order to classify the types of glass, this paper first uses Fisher linear discriminant analysis to obtain a binary classification model of glass types, and finds that the prediction accuracy of the model has reached 90%. Considering the possible overfitting of the model, this paper also uses the principal component analysis method to reduce the dimension of the data, thus obtaining the model and determining that its accuracy rate is maintained above 90%. In order to identify the types of unknown glass cultural relics, the multi-category Fisher’s Linear Discriminant method based on principal component analysis was used to identify the subcategories they belonged to.
Review of Dielectric elastomer based application for Soft robotics
Authors: Luo Haiyang , Lai Feiran , Yang Wen , Xu Yuqin , Xie Zhifei , Li Jiaping , Luo Ziyi , Chen Hongzhao
Published: April 2023

Soft robotics is a growing field that is getting more and more attention. Unlike traditional rigid robots, soft robots have a simpler structure and control logic, a simple electric voltage change can activate the whole control system, with the capability of carrying out more complex tasks at the same time. Dielectric elastomer is thought to be a fundamental technology advancing the development of soft robots, with the advantages of fast response, great stretch capacity as well as resilience, less weight and higher energy density. Dielectric elastomer technology has many practical applications, such as grippers, robots on ground, swimming robots, artificial body tissues and so-called artificial muscles. In this paper, we mainly introduce the state-of-art application of Dielectric elastomer in the soft robotics field and also discuss the challenges that the DE-based soft robotics are encountering.
Analysis and identification of ancient glass cultural relics based on fuzzy C-mean clustering
Authors: He Gongcheng , Zhao ZeLin , Lin Yujie
Published: April 2023

Glass is a valuable physical evidence of ancient Silk Road trade, and ancient glass in China was made locally by absorbing its technology, and it is difficult to distinguish from foreign glass products in appearance, but the internal chemical composition of the two is different. Therefore, this paper focuses on the chemical composition data of the collected ancient glass artifacts, and uses fuzzy C-means aggregation to analyze and identify the composition of ancient glass. The results show that the classification of ancient glass artifacts using fuzzy C-mean clustering is reasonable. The experimental results and experimental data processing methods provide a new way to study ancient Chinese glass artifacts.
Decision tree based classification of glass artefact types
Authors: Yu Hai
Published: April 2023

This paper uses logistic regression, SVM, and decision trees in machine learning to analyse 67 data items from question C of the 2022 GCSE Cup National Student Mathematical Modelling Competition. The data were analysed using systematic clustering, the clustering coefficients were analysed, the number of clusters K was further determined by the "elbow" method, a clear classification pattern between the glasses was obtained, and a grid search method was used to classify the glasses. The results show that the new excavated glass artefacts have been classified using the "elbow" method. The results show that newly excavated glass artefacts are classified by varying PbO content. If the lead oxide (PbO) content is below 5.46%, they are considered high-potassium glasses and vice versa for lead-barium drinks. The content of silica was further used as a boundary to divide the high-potassium glass into two subclasses. Lead-barium glasses are divided into three subclasses using the lead oxide and silica content as the boundary. Using a series of models and algorithms, the classification patterns of different types of glass and their subclasses were clarified, and the results were tested for reasonableness and sensitivity. Such a model can be used to classify newly excavated glass artefacts and can also be modified based on this model for the identification and analysis of other ancient artefacts.
Chemical composition analysis of ancient glass products based on decision tree
Authors: He Zhihao , Qin Weiduo , Duan Changping
Published: April 2023

Due to the effects of prolonged burial, freshly unearthed ancient glass is often weathered to varying degrees, and it is difficult to identify the type of glass. We introduce machine learning into the composition analysis and type identification of ancient glass products. This objective is to build a reliable ancient glass classification model based on decision trees and two different k-means clustering algorithms. The performance of the decision tree is measured by the ROC curve. The performance of its clustering algorithm was evaluated by the Calinski-Harabasz index. The results show that the area of AUC in the decision tree is 1 and the highest Calinski-Harabasz index of the two clustering algorithms is 71.68. The predictive ability of the model was verified well.
Forest management plans based on carbon sequestration models
Authors: Yang Siyuan , Wang Wenfei , Yun Yizhuo , Liu Yutong
Published: April 2023

Carbon sequestration is one of the most important ways to sequester carbon dioxide from the atmosphere to reduce the amount of greenhouse gases in the atmosphere, and forests play an indispensable role in the carbon sink. This paper will use time series prediction model (ARIMA) to Iceland, France and Italy is located in three different latitude, different climatic zone of European countries for predicting the forest carbon sequestration, change model perfectly through stationarity test sequence, and the predicted results are the residual analysis, and finally use AHP to construct a judgment matrix, obtain the weight vector through normalization, conduct consistency test, and establish an evaluation model to measure the five aspects of carbon sequestration, water and soil conservation, biodiversity, wood product profits and benefits, and social services. In the end, this paper gains the weight of the main factors affecting forest value. This paper explains to community dwellers the need for moderate deforestation of forest trees based on the above model and conclusions.
Glass classification and identification based on Lasso-logistic model and K-means clustering
Authors: Chen Hesheng , Fan Wenya , Zhang Lanxin
Published: April 2023

Ancient glass is highly susceptible to weathering by the burial environment, with a large number of internal elements exchanging with environmental elements, resulting in changes in the proportions of their composition. In order to analyse the classification patterns of High potassium-rich glass and Lead and barium enriched glass, and to classify each type of glass into appropriate subcategories, Decision tree was first chosen to broadly classify the decision factors for the glass types, and then lasso-logistic was chosen for the exact solution. K-means clustering was used in combination with Factor Analysis Method to achieve subcategories for both types of glass. Finally, using the above model, the chemical composition of the unknown glass is used to identify the type.
Whether the spread of disease is related to wildlife trade -- correlation analysis based on world wildlife trade data
Authors: Liu Yizhou , Wang Shizhe
Published: April 2023

The wild animal market is suspected to be the source of the current epidemic and the SARS epidemic in 2002, and the consumption of wild meat is considered to be a source of Ebola virus in Africa. In order to study whether the spread of disease is related to wildlife trade, this paper analyzes the wildlife trade volume in the year of SARS and COVID-19 outbreak from the perspective of time. The results show that the trade volume of scientific animals has increased significantly in the 2003 and 2020. From the biological point of view, we searched for some famous diseases and combined the annual epidemic data with the transaction volume of laboratory monkey. Through the analysis of the line chart, we concluded that the transaction volume of laboratory monkey has a certain correlation with the major epidemic, and then extended the conclusion that there is a certain relationship between the wildlife trade and the major infectious disease epidemic.
Prediction of global temperature based on the BP neural networks
Authors: Huang Zhonglin , Wang Junjie , Gongbo Zedan , Li Qiao , He Yutong
Published: April 2023

The problem of global warming is getting worse as global temperature has risen year by year to an alarming level. This paper is first based on historical data on global temperatures, two prediction models were developed using Gray Prediction Method and BP Neural Network model, whose results show that the root mean square error test value of BP neural network is about 0.03 lower than that of the gray prediction method (0.1627).Thus, the BP neural network prediction model is proved effective, and then the model was analyzed by gray correlation theory, which found that carbon dioxide concentration, forest cover area and human population are affecting the global temperature, and the Gray correlation of the fisrt two factors is as high as 0.8, which makes the two the main factors. In the end the paper gave measures to contain global warming.
Classification and identification of glass based on principal component and systematic cluster analysis
Authors: Liu Wenjie , Zhang Kuntan , Ma Xinran
Published: April 2023

The composition of glass relics in different regions is not completely the same. Meanwhile, due to the large amount of internal elements exchanged in the process of glass burial and weathering, in order to determine and find a method to classify and identify glass relics, principal component analysis and systematic clustering are used to select the appropriate indexes for clustering by selecting the composition indexes of existing glass samples. The types of unknown glass artifacts are determined by classification from the types of known glass artifacts. Finally, after multiple cluster analysis, two unknown types of glass relics were identified as high potassium and lead barium. After the identification, the glass chemical composition data were fine-tuned up and down, and it was found that the identification type remained unchanged and the identification effect was stable and accurate.
Classification and Prediction of Ancient Glass Artifacts based on Chi-square Test
Authors: Chen Yifan , Nie Jiayi , Xu Ke
Published: April 2023

This paper focuses on the composition analysis and type identification of ancient glass objects. The correlation between the weathering of the surface of glass artifacts and its type, color and decoration is obtained by establishing a chi-square test model based on the characteristics of fixed class variables. After that, the prediction model was established based on the weighted average method according to the characteristics of the data, and the predicted value of each chemical composition before weathering was solved.
A glass classification model for glass artifacts based on PCA and SVM
Authors: Nie Jiayi , Xu Ke , Chen Yifan
Published: April 2023

The Silk Road was an important channel for trade and commerce between East and West in ancient times, and an important link for cultural exchange between East and West, playing an important role in the development of ancient civilization and history. Glass was one of the important goods carried on the Silk Road in ancient times. In this paper, focus on the problem of component analysis and type identification of ancient glass products. This paper extracted the important factors of the data by PCA principal component analysis, reduced the 14-dimensional data to two dimensions, then built a data point distribution map by visualization, and established a linear classification model based on SVM support vector machine. After that, the model is used to identify the type of samples based on the underlying data. The sensitivity indices of each factor were solved by using Sobol method for the sensitivity analysis of the results.
Based on Machine Learning Classification Correlation Study and Species Classification of Glass Artifact Under the Influence of Weathering
Authors: Wang Jingyi , Li Xueqing
Published: April 2023

The five thousand years of Chinese culture has congealed countless crystallization of wisdom, and glass is also one of the products. However, because in ancient times the technology of the China glass production failed to reach the current level, it is highly susceptible to be weathered by the burial environment. The paper provides theoretical support for the archaeological study of ancient glass by correlating the relationship between surface weathering and the features of glass artifacts and by exploring the classification rules of ancient glass of known glass varieties (lead-barium glass and high-potassium glass). For the relationship between color and surface weathering, the most suitable AHP model is selected in the paper, while the importance scale of AHP is quantified by combining the physical model. Secondly, the Kendall coefficient consistency test model was used to analyze the correlation between glass varieties and surface weathering. Finally,the chi-square test model was used to analyze the correlation between ornament and surface weathering. The paper draws a conclusion that the surface weathering of glass relics has more correlation with its color, the deeper the color, the greater the possibility of surface weathering; the correlation between lead-barium and weathering is high; and the degree of correlation between glass ornamentation and weathering is very low in agreement.In view of the classification problem, the paper uses linear discriminant analysis (LDA) to establish a linear classifier and quantify the classification rule, in order that data with low frequency are not reduced, so as not to truly reflect the classification law, and finally the paper obtains a linear classifier with accurate classification.
Study on Chemical Composition of Ancient Glass Based on Standardized Model
Authors: Deng Yanduo , Feng Chuanrui , Zhang Qingyang
Published: April 2023

In the study of ancient glass, identifying its chemical composition is an indispensable step to accurately classify it. However, the weathering of ancient glass in the buried environment will change the chemical composition, so the ability to properly process data such as chemical composition is crucial. In this paper, the relationship between the weathering of high-potassium glass and lead-barium glass and its color and pattern is studied respectively, and the existing data on the chemical composition of the sample glass in cultural relics are processed and analyzed by constructing a standardized model. Besides, the non-weathered standardized models of high-potassium glass and lead-barium glass were obtained, and their weathering trends were summarized. Based on this model, the chemical composition content of samples before weathering was predicted.
Composition analysis and identification of ancient glass based on K-Means clustering
Authors: Dong Keju
Published: April 2023

The analysis and research on the composition of ancient glass is widely used in the reduction and identification of the composition of archaeological relics. In this paper, the relevant data of CUMCM2022 problem C is used to establish a mathematical model, and multiple linear regression, binary logistic regression and K-means clustering algorithms are used to realize the systematic analysis of the chemical composition of cultural relics, and solve the problem of predicting the classification of cultural relics. In the study of ancient glass classification, multiple linear regression and binary logistic regression are used to transform abstract text data into intuitive multiple linear regression equation, and a relatively ideal classification law is obtained. According to the change rate of chemical composition before and after weathering of various kinds of glass, the appropriate chemical composition was selected as the classification index, and the elbow method and K-means clustering were used to obtain the distinctive subclassification results. Finally, the sensitivity of K-means clustering subclassification model is analyzed by numerical perturbation method, and the model shows high stability.
Classification and Identification of Ancient Glass Objects based on K-means++ and Fisher Discriminant
Authors: Du Yuchao , Zhou Jie , Li Jingxuan
Published: April 2023

The significance of this study is to classify and identify the types of ancient glass products according to their chemical composition. The data were selected from the proportion of chemical compositions that have been analyzed for ancient glass, and the best number of clusters (k) for the division was roughly determined using the elbow rule for the five chemical compositions of high potassium and lead barium, respectively, and brought into the k-means++ algorithm for cluster analysis, and then the final determination of k and the evaluation of the rationality of clustering were performed using the contour coefficient, and finally the Fisher discriminant analysis method based on variable meritocracy combined with eigenvalues, Wilke Lambda, and classification function coefficients to identify unknown categories of glass artifacts. The model used was analyzed and evaluated with good results, and the model is applicable to the classification of ancient glass artifacts and identification of the type to which they belong.
Component Analysis Model of Glass Relics Based on Logistic Regression and Fisher Linear Discrimination
Authors: Xu Jiayan , Shi Chenfei , He Chenyuan
Published: April 2023

In recent years, with the attention paid by various countries to the exploitation and protection of cultural relics and the continuous development of industrialization, people have gradually realized the necessity of analyzing the weathering of ancient glass relics. In this paper, the physical characteristics, chemical composition and content of sample cultural relics are analyzed and their types are identified by using multiple algorithms such as Logistic regression model, Fisher linear discrimination, Fisher’s exact test, etc. The study of this issue can provide guiding suggestions for the analysis and classification of ancient cultural materials, and help archaeologists carry out a series of work such as cultural relics protection. The results show that the "type" factor has the greatest relationship with weathering, followed by "color" and "decoration". The regression equation between the sample and weathering chemical composition is established, and it is concluded that "type" and "SnO2" have a large negative correlation with weathering, "MgO" and "SO2" have a large positive correlation, and other variables have a weak correlation. Finally, Fisher linear discriminant method is used to identify the category of unknown glass relics. By estimating the training group and testing the test group, it is found that the algorithm can correctly classify 100.0% of the original grouped cases. We can identify the unknown cultural relics and find that A1, A5, A6 and A7 cultural relics belong to high potassium glass, and the rest belong to lead barium glass. In order to test the accuracy of the model in identifying the category of glass relics, Fisher's exact test algorithm was used. It was found that the classification results were more sensitive to silica in the fluctuation range of - 50% to - 25%, and less sensitive to other chemical components, it is stable.
Optimal design of wave energy maximum output power based on simulated annealing algorithm
Authors: Lv Xin , Shang Zheyu
Published: April 2023

As one of the largest new energy sources, wave energy has received a lot of attention from governments in various countries. In recent years, researchers in various countries have done a lot of work on the collection and conversion of wave energy, and the utilization of wave energy is getting higher and higher. The problem of further optimizing the wave energy harvesting device can be solved by using optimization algorithms, which need to be intelligent due to the complexity of the problem. The simulated annealing algorithm is a classical intelligent optimization algorithm that can perform global optimization of the objective function with excellent results. In this paper, the output power of float-vibrator type wave energy devices is optimized using the simulated annealing algorithm, and the optimal values of important parameters are obtained, which play a reference significance for practical development.
Chemical compositions prediction of glass artifacts based on logistic regression and linear weighting
Authors: Zuo Kewen , Yang Yi , Li Xingyu
Published: April 2023

Chemical composition analysis is of great significance for studying the category, origin and production age of the ancient glass. In order to consider the influence of weathering on chemical composition, this paper proposes a prediction method of glass chemical composition based on logistic regression and linear weighting. First, the chi-square test shows that whether the glass surface is differentiated is related to the type of glass. Secondly, the chemical composition of glass relics is divided into two categories by binary logistic regression: significantly affected by weathering and not significantly affected by weathering. Then, for the chemical components not significantly affected by weathering, combined with descriptive statistical results, the mean value was used as the chemical composition content before weathering. For the chemical components significantly affected by weathering, the linear weighting method was used to predict the content of chemical components before weathering. The final results show that this method can better reflect the influence of weathering factors on the chemical composition of glass, which is of great significance for the prediction of the glass composition.
Research on soil moisture prediction based on VAR-ARIMA model
Authors: Wen Xin , Wei Juan , Zhang Jinyang , Yue Junrong
Published: April 2023

This study uses precipitation, soil moisture and evapotranspiration data as independent variables to predict future soil moisture in the Xilingol grassland of Inner Mongolia, China, while keeping the grazing strategy unchanged. Firstly, the data with anomalous values in the obtained dataset were differenced, and the soil moisture data for different depths were split to build a multi-group ARIMA prediction model. The reliability of the model was determined to obtain the soil moisture in grassland at different depths from 2022 to 2023. Through this study, we have added VAR to the ARIMA model to improve the limitations of predicting future soil moisture based on a single variable and to improve the accuracy of soil moisture prediction, thus providing some theoretical support for the ecological restoration and sustainable development of grasslands.
5th International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2023)
Authors: Jiang Yuqing , Cromwell Augus
Published: April 2023

2023 5th International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2023) was successfully held from 25 to 26, February, 2023 in Rio, Brazil. The conference was jointly organized and sponsored by Harbin Institute of Technology and China University of Geosciences, the conference invited scholars and experts in the fields of materials science, mechatronics, mechanical engineering, and energy engineering from various universities and institutes, to participate in the review and guidance of this conference.

MSMEE 2023 focuses on the latest research fields and aims to provide an international cooperation and exchange platform for experts, scholars and business managers to share their research achievements, discuss the key challenges and research directions, and jointly promote the industrialization cooperation and continuous innovation of international academic achievements. This collection of proceedings compiles oral and paper presentations submitted by the authors and scrutinized by the special committee. The format of questioning and discussion was that after each author’s introduction, the conference chairman and committee members asked and answered questions.

The organizing and editorial committee of the MSMEE 2023 hopes you enjoy the reading of this volume. Besides, we wish to thank all authors and participants for providing their valuable contributions for this proceeding as well as the reviewers for their constructive recommendations and criticism aiding to improve the presented articles. We are confident that this issue will serve as a reference for experts, scholars and enterprise managers in the fields of materials science, mechatronics, mechanical engineering and energy engineering.

With best regards,

MSMEE Technical Program Committees

Rio, Brazil
Definition and forecasting of GGDP in the landscape of climate issues
Authors: Sun Yujie , Gao Leyan , Shen Ruiyang
Published: April 2023

In this paper, we propose a GGDP assessment system for climate mitigation, analyze its ecological impacts, and discuss the potential advantages and disadvantages of the GDP transformation. Firstly, the definition and traditional calculation of GGDP are elaborated, and eight indicators are divided into direct and indirect factors for climate mitigation. Then, five rep-presentative countries are selected and the data of indicators are substituted. Besides, the weights corresponding to the indicators are calculated by the entropy weighting method and the coefficient of variation method respectively. Next, the comprehensive weighting coefficients of the indicators are figured out by the combined method. The established GGDP system based on the CV-EWM evaluation model is used to obtain the GDP and GGDP change of five countries from 2001 to 2022. Additionally, the BP neural network algorithm is used to predict the trends of CO2 and temperature under the two systems of GDP and GGDP, respectively. Finally, the neural network was optimized by a genetic algorithm to establish the global climate impact assessment model based on GA-BP neural network prediction, and the global effect of the GGDP system on climate mitigation issues was studied.
Energy Saving E Butler - an Integrated Device for Predictive Regulation Based on Smart Buildings
Authors: Zhoum Chaorui , Lv Zhengxin , Wang Lujia , Xin Yu , Zhang Zijie , Wu Jiahua
Published: April 2023

As of today, "carbon emission exceeds the standard" has seriously affected people's life, and it has become the responsibility and obligation of every citizen to monitor and reduce the carbon emission beam. At present, China is the world's largest construction market, and most of the new buildings are still high-energy buildings, and the proportion of building energy consumption is increasing. Nowadays, China's economy and society are developing in the direction of low-carbon economy and green environment protection. Therefore, this paper develops an "integrated system of predictive control based on smart building", which first classifies the people in the building by statistical methods, and then constructs the demand curves of different people for each control parameter in the building through the people behavior model. Based on the demand curve, the optimal control scheme for energy saving in the building is made on the premise of meeting the demand of most people for environmental comfort, and then the optimized control parameters are applied to the actual regulation through a series of sensors and control elements to realize fully automatic control of the building facilities.
Effect of Nb5+ doping on microwave dielectric properties of MgTa2O6 ceramic
Authors: Shi Liang , Liu Cheng , Zhang Huaiwu
Published: April 2023

As the main carrier for microwave circuits, microwave dielectric ceramics are receiving a lot of attention as the main carrier for the current 5G and pre-developed 6G communication technologies. A series of Nb5+ doped MgTa2O6 ceramics were synthesized by the solid-state reaction method X-ray diffraction confirmed that a single tetragonal structure can be formed when the doping amount is lower than 0.03, a heterogeneous structure of tetragonal and orthorhombic crystal structure is formed when the doping amount is lower than 0.15, and the tetragonal structure is completely transformed into orthorhombic structure when the doping exceeds 0.15. SEM results also show the transformation process of the grains of tetragonal structure to orthorhombic structure. The optimum microwave dielectric properties were obtained for 9% Nb5+ doped samples: εr = 24, Q×f = 71,000 GHz (at 8.9 GHz), TCF = 15 ppm/oC.
Research on optimization test of electrode material in desulfurization wastewater purification system of coal-fired power plant
Authors: Wang Xiaohui , Song Chunyan , Gao Yan , Liu Xiao , Shi Xian
Published: April 2023

The traditional coal-fired power plant wastewater treatment technology is faced with the problems of complex system, high operating cost, easy scaling and corrosion, etc. Therefore, coal-fired power plants need to adopt an integrated multi-functional coupling system, taking into account the desalination, anti-scaling, etc. function to remove pollutants from wastewater. Electro-adsorption technology is a technology that can realize water purification and water desalination. It is a new type of water treatment technology. It can effectively remove impurity ions in water without scaling under the premise of low energy consumption. In this paper, the development history of electrosorption theory, the principle of electrosorption, the main points of electric double layer theory, the structure of electrosorption and its working process are reviewed. Several main electrode materials and their advantages and disadvantages are introduced in this paper. Based on the increasingly stringent environmental protection requirements, electro-adsorption technology is expected to be widely used in the power industry due to its advantages of low energy consumption, low cost, and no secondary pollution.
Development of nanomaterials in flexible electronics
Authors: Chi Aobing , Zhang Enming , Hang Xu
Published: April 2023

Flexible electronics, with its excellent flexibility, leading-edge and lightweight, has become a frontier technology capability in the field of electronics, which integrates well with the characteristics of nanomaterials for applications in various disciplines such as sensors, information, medical, and energy. This paper systematically summarizes the main structures of flexible electronics featuring flexible substrates with their outstanding flexibility as well as mechanical and electrical properties. Afterwards, it delves into the four major properties of nanomaterials along with their extensive applications aboard flexible electronics. In particular, the development applications of carbon nanotube films in sensors and electronic devices by means of their great flexibility and electrical conductivity are mainly outlined. Then the practical applications of graphene in the domain of electronic displayer through its superior heat dissipation are introduced. In the final part, an exploration is made on how the advantages of flexible electronics and nanomaterials can be further used in frontier fields such as aerospace, smart medicine, and automated science if we combine them more effectively. However, as an emerging field, the development process of flexible electronics is still fraught with challenges. Two major challenges are still facing the field: mechanics, packaging, and cost. There is a long way to go for flexible electronics combined with nanomaterials, which can open numerous possibilities for electronic technology.
Numerical investigation of the influence of the nozzle bump on nozzle flow
Authors: Ge Jinghan , Mao Yuhe , Wu Ruihan , Zhang Chongchu
Published: April 2023

Fluid Mechanics is the study of liquid or gas performance in motion or at rest. Many of the engineering disciplines apply fluid mechanics principles and concepts. With the development of technology, computer is involved in the field, which leads to computational fluid dynamics. In this paper, nozzles with various shapes of bump are used as the research object to investigate the influence of the bump on the nozzle flow via small disturbance approximation. Specifically, triangular, parabolic, irregular and combined shapes are utilized. Two different situations are also included in this paper, which are subsonic and supersonic case. The experimental results demonstrated that within reasonable parameters as the variable increases, the change becomes clearer. When area decreases in the same shape, the streamlines become fluctuant more extremely, especially the one near the boundary. The assumption that the fluid flows disorderly near the bottom is also verified by the simulation.
Research Progress on Improving Photovoltaic Conversion Efficiency in Lunar Rovers
Authors: Gao Mingren , Lin Jianjie , Liu Zhuowei
Published: April 2023

With the deepening of human exploration of the moon, the requirements for essential technology applications such as the energy reserve of the lunar rover have also increased. Moreover, a steady supply of energy is what the moon rover needs, and how to obtain a reliable energy supply is also a concern of humans. Improving solar energy conversion efficiency is a feasible way to solve this problem. The paper reviews the measures and research progress of improving the solar energy conversion efficiency of the lunar vehicle. Firstly, analyze the selection of solar photovoltaic panel materials, and introduce the research and selection of various materials. Secondly, summarize the methods to reduce the amount of lunar dust in contact with solar panels. Lastly, analyze the design of solar panel structure, the insolation efficiency under different systems, the control principle, and its characteristics.
Key technologies for photovoltaic power generation
Authors: Liu Wenrui
Published: April 2023

In the face of the increasingly serious energy and environmental problems in the world, it is imperative to develop renewable energy, including photovoltaic power generation. The fact that photovoltaics is still in their infancy suggests that they have a lot of potential. Wide-ranging potential for solar power generation opens up a lot of room for the advancement of photovoltaic technology and industrial growth. Solar energy is mainly used for photovoltaic power generation system (PV system). Its main components are solar cells, batteries, controllers and inverters. Solar cells and MPPT technology are the two main structure in PV system. The development of solar photovoltaic power generation is the premise of the development of photovoltaic technology, because he is an important element of photoelectric conversion, which is related to the energy conversion of the entire system. MPPT voltage is a very critical parameter in the design of photovoltaic power plants. In this article, advantages and disadvantages of four different types of solar cells and their improvement methods will be exponded, while the MPPT technology starts from the traditional algorithm and the intelligent algorithm, with the introduction of several different algorithms. The final prospect of the two key technologies is given at the end of this paper.
Status and Progress of the Retired Power Batteries Recycling in the Context of “Double Carbon”
Authors: Qiu Yangchen
Published: April 2023

In recent years, to promote goal of "carbon peaking and carbon neutrality", replacing the traditional vehicles by electric vehicles becomes the essential solution to reduce the environmental pollution. The power battery, as the power source of electric vehicles, is also one of the core components of new energy electric vehicles. As an important part of the future development of pure electric vehicles, the decommissioning process of power battery recycling is summarized and analyzed from the current situation of decommissioned power batteries, the relevant standards and policies of power batteries in recent years, and the development and utilization of two kinds of decommissioned power batteries: dismantling and recycling and secondary utilization, respectively, and for the secondary utilization process, the focus is on the residual energy detection process and the screening and reorganization application scenarios. Finally, relevant suggestions are given to provide ideas for the green development of retired power batteries under the dual carbon target of "carbon peaking and carbon neutral”.
Application Status and Difficulties of Fuel Cell Technology
Authors: Zhang Mohan
Published: April 2023

With the gradual deterioration of the earth's environment, human is now facing numerous problems, environmental protection has become a hot topic and key problem in the present era. Compared with internal combustion engines, fuel cells have more fuel options. It can use hydrogen as it’s fuel, which has the advantages of non-pollution, high specific energy and high efficiency. Hydrogen has been proposed as a new alternative energy source for many years, thus the theory is well established, s, the formation of related industries will be relatively easy. This paper summarizes the application status and technical difficulties of fuel cells, analysed the possible promotion direction in the future. In conclusion, fuel cell has a promising development and market prospect, it is now developing rapidly in the field of passenger vehicles, while other industries still have broad prospects. Also, there are many problems such as catalyst attenuation, high cost, storage and transportation.
State of the Art Wireless Charging Technology for Electric Vehicles
Authors: He Xinyu , Shen Haomin , Wang Lukuan
Published: April 2023

Wireless charging technology for EV (electric vehicles) is a trend in the car of the future Because it is a bit significant, such as driving with no emissions at all. When decelerating, the energy can be repeated in life. Noise and vibration are low. The core technology of electric vehicles lies in the "three electric" system, namely electric drive system, battery system and electric control system, these three systems constitute the key technology of electric vehicle. The advantage of wireless power transfer technology is that the weight and volume of the power system are significantly reduced, and the versatility and reliability are high. In this paper, wireless charging technology is divided into magnetic induction transmission and electric field coupling transmission. The research status and focus of this technology are summarized from the aspects of transmission coil, compensation network, power electronic converter and its control method. Finally, the compelling places and future directions of wireless charging technology are discussed Introduction.
Comprehensive Analysis of the Advanced Technologies for Scramjet
Authors: Jiang Baohong
Published: April 2023

Scramjet is a kind of aspirated engine, where oxygen in the atmosphere is used as oxidant to react with fuel in fuel bunker. Structural components are used in the scramjet to generate shock waves at high speed to compress the high-speed air flow, and realize the deceleration and pressurization of the air flow, which is different from engines where air compressors are used. Technologies related to the scramjet power/fuel are presented, and the features related to this kind of engines are highlighted in this paper. The development process of the scramjets in the application field both home and abroad is overviewed. The problems involved with scramjets in hypersonic vehicle application, combined cycle power system, design of thermal protection structures and high temperature materials are discussed. The critical technologies of scramjets, i.e., tail nozzle, combustion chamber, air inlet, fuel selection etc. are identified. The features of hydrocarbon fuel and its application in hypersonic vehicles are summarized. And the progress of research of the relevant technologies and personal prospects for scramjets are briefly described.
State of the Arts of Hydrogen Fuel Cell Vehicles
Authors: Xu Jinchao
Published: April 2023

With the rapid development and progress of science and technology, people are doing more and more serious damage to the earth. Hydrogen energy, a pollution-free energy, has naturally become the main research object. Hydrogen energy is a kind of secondary energy, which needs to be produced by some specific methods. Hydrogen fuel cell vehicles becomes one of the key new energy automations in both academia and industry, considering the eco-friendly capability. In this paper, the development of hydrogen fuel cell vehicles is comprehensively introduced, and the related characteristics of hydrogen energy, hydrogen fuel cells work are discussed. Meanwhile, the use of hydrogen fuel cell car and challenges, analysis of the cases of several existing hydrogen fuel-cell cars and hydrogen fuel cell vehicles in China in the future are given in this paper. Finally, a personal vision of the future of hydrogen fuel electric vehicles is conclusion in the end of this paper.