In recent years, great changes have taken place in economy and society in China. However, income inequality is becoming more serious and it needs to be paid more attention. Therefore, the analysis of factors that affect income is important. The Bayesian network is a common method to study causal relationships among different variables. The paper analyzed personal annual income in 2016 in China based on the data of Chinese General Social Survey (CGSS) with the Bayesian network (BN). The research is to study the relationships among 14 income related factors and classify the personal income level. Based on the per capita disposable income in 2016 in China (23821 yuan), personal income was divided into two categories: High Income (personal income was greater than 23821) and Low Income (personal income was smaller than 23821). Then we applied BN to classify the level of personal income. The predicted classification results with Bayesian network were compared with those with Naïve Bayesian method. It could be found that BN could not only reflect the causal relationships among 14 variables, but also have higher prediction accuracy in this income problem.
{"title":"The Classification of Chinese Personal Income Level Based on Bayesian Network","authors":"Lei Li, Xueli Wang, Juan Yang","doi":"10.1145/3545839.3545856","DOIUrl":"https://doi.org/10.1145/3545839.3545856","url":null,"abstract":"In recent years, great changes have taken place in economy and society in China. However, income inequality is becoming more serious and it needs to be paid more attention. Therefore, the analysis of factors that affect income is important. The Bayesian network is a common method to study causal relationships among different variables. The paper analyzed personal annual income in 2016 in China based on the data of Chinese General Social Survey (CGSS) with the Bayesian network (BN). The research is to study the relationships among 14 income related factors and classify the personal income level. Based on the per capita disposable income in 2016 in China (23821 yuan), personal income was divided into two categories: High Income (personal income was greater than 23821) and Low Income (personal income was smaller than 23821). Then we applied BN to classify the level of personal income. The predicted classification results with Bayesian network were compared with those with Naïve Bayesian method. It could be found that BN could not only reflect the causal relationships among 14 variables, but also have higher prediction accuracy in this income problem.","PeriodicalId":249161,"journal":{"name":"Proceedings of the 2022 5th International Conference on Mathematics and Statistics","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114289768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I. Mukhlash, Athyah D. S. Gama, Mohammad Iqbal, D. Darmaji, M. Kimura
One common action to keep aware of the current investment progress is by updating finance news continuously. Indeed, we can read a bunch of news relating to finance from social media, which is often difficult to figure out at a glance. Hence, this work aims to propose hybrid models that can help us to classify whether the finance news is positive to follow. Also, we may sort a few articles containing neutral ones. More specifically, we incorporate deep neural networks: deep convolutional neural networks and long short term memory, to draw diverse word representations, and support vector machines to categorize them as a multi-class classification case. In this work, we evaluated the proposed models on Indonesian finance news that was officially reported from the Bank of Indonesia around 2019 before the pandemic started. In the evaluation results, we showed the DCNN-SVM better accuracy compared to others.
{"title":"Indonesian Finance News Sentiment from Hybrid Deep Learning and Support Vector Machine","authors":"I. Mukhlash, Athyah D. S. Gama, Mohammad Iqbal, D. Darmaji, M. Kimura","doi":"10.1145/3545839.3545858","DOIUrl":"https://doi.org/10.1145/3545839.3545858","url":null,"abstract":"One common action to keep aware of the current investment progress is by updating finance news continuously. Indeed, we can read a bunch of news relating to finance from social media, which is often difficult to figure out at a glance. Hence, this work aims to propose hybrid models that can help us to classify whether the finance news is positive to follow. Also, we may sort a few articles containing neutral ones. More specifically, we incorporate deep neural networks: deep convolutional neural networks and long short term memory, to draw diverse word representations, and support vector machines to categorize them as a multi-class classification case. In this work, we evaluated the proposed models on Indonesian finance news that was officially reported from the Bank of Indonesia around 2019 before the pandemic started. In the evaluation results, we showed the DCNN-SVM better accuracy compared to others.","PeriodicalId":249161,"journal":{"name":"Proceedings of the 2022 5th International Conference on Mathematics and Statistics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130474014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Long-jumpers’ performances are affected by various factors. Based on the physical characteristics, take-off angle, approach speed, air density of environment, etc., this paper establishes a mathematical model that can obtain the long-jumpers’ theoretical long jump performance. The conclusions are as follows: (1) Air resistance has almost no effect on the athlete's long jump performance. (2) The faster the approach speed leads to better results. (3) Theoretically, the take-off angle is proportional to the distance for long-jumpers cover, but high take-off angle will unbalance the body, resulting in a greater loss of speed, and reduce the performance. The model in this paper has very small errors and has good applicability. It is recommended that athletes increase the approach speed and increase the take-off angle on the premise of maintaining body balance.
{"title":"Research on the Factors Influencing Long Jump","authors":"Zijian Shang","doi":"10.1145/3545839.3545845","DOIUrl":"https://doi.org/10.1145/3545839.3545845","url":null,"abstract":"Long-jumpers’ performances are affected by various factors. Based on the physical characteristics, take-off angle, approach speed, air density of environment, etc., this paper establishes a mathematical model that can obtain the long-jumpers’ theoretical long jump performance. The conclusions are as follows: (1) Air resistance has almost no effect on the athlete's long jump performance. (2) The faster the approach speed leads to better results. (3) Theoretically, the take-off angle is proportional to the distance for long-jumpers cover, but high take-off angle will unbalance the body, resulting in a greater loss of speed, and reduce the performance. The model in this paper has very small errors and has good applicability. It is recommended that athletes increase the approach speed and increase the take-off angle on the premise of maintaining body balance.","PeriodicalId":249161,"journal":{"name":"Proceedings of the 2022 5th International Conference on Mathematics and Statistics","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125662947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The research on all-or-nothing transform in cryptography leads to the problem that, for a given positive integer , what is the density of invertible submatrices of any invertible matrix? For binary matrices, previous work shows that in the case , , where denotes the maximum proportion of invertible submatrices in invertible matrices. In this paper we study the case . It is proved that and an upper bound of is given as well.
{"title":"Evaluation of the maximum proportion of invertible submatrices in invertible binary matrices","authors":"Jiayi Hu","doi":"10.1145/3545839.3545843","DOIUrl":"https://doi.org/10.1145/3545839.3545843","url":null,"abstract":"The research on all-or-nothing transform in cryptography leads to the problem that, for a given positive integer , what is the density of invertible submatrices of any invertible matrix? For binary matrices, previous work shows that in the case , , where denotes the maximum proportion of invertible submatrices in invertible matrices. In this paper we study the case . It is proved that and an upper bound of is given as well.","PeriodicalId":249161,"journal":{"name":"Proceedings of the 2022 5th International Conference on Mathematics and Statistics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129348288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We explore and contrast two distinct ways of extracting discrete predictive models for the evolution of stock market time-series data. In particular, the two methods for constructing models are one, applying the commonly used “hollow candlestick” framework to the time series data on the daily level and feeding the result into a Markov chain inference module in R; two, applying the popular technical indicator “Fibonacci extension levels” to a filtered time-series data, then transcribing the price movements into a sequence to be fed into the same Markov chain inference module. Whereas continuous-time stochastic models are well studied and widely deployed in the computational trading industry and among econometrics scholars, models that are discrete in nature remain extremely popular among professional and amateur traders. In this paper, we set out to apply formal statistical methods to two discrete trading models to gain a better understanding of their predictive power and utility.
{"title":"Markov Process Modeling on Derived State Spaces of the Price Dynamics of Stock Market Indices","authors":"Bohan Li","doi":"10.1145/3545839.3545850","DOIUrl":"https://doi.org/10.1145/3545839.3545850","url":null,"abstract":"We explore and contrast two distinct ways of extracting discrete predictive models for the evolution of stock market time-series data. In particular, the two methods for constructing models are one, applying the commonly used “hollow candlestick” framework to the time series data on the daily level and feeding the result into a Markov chain inference module in R; two, applying the popular technical indicator “Fibonacci extension levels” to a filtered time-series data, then transcribing the price movements into a sequence to be fed into the same Markov chain inference module. Whereas continuous-time stochastic models are well studied and widely deployed in the computational trading industry and among econometrics scholars, models that are discrete in nature remain extremely popular among professional and amateur traders. In this paper, we set out to apply formal statistical methods to two discrete trading models to gain a better understanding of their predictive power and utility.","PeriodicalId":249161,"journal":{"name":"Proceedings of the 2022 5th International Conference on Mathematics and Statistics","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124642707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the development of educational informatization, the adoption and diffusion of educational technology have become hot research. As educational technology innovation, the MOOC has opened the "Internet + Education" integrated teaching model, and it realized the sharing and diffusion of college educational resources around the world. This paper selects MOOC as the research object and explores the educational technology diffusion, diffusion characteristics, and diffusion process of MOOC based on the innovation diffusion theory. Through the construction of the Bass model, the diffusion process of MOOC in the recent 10 years is analyzed from an objective perspective, and the future diffusion trend of MOOC is predicted.
{"title":"Analysis of Technology Innovation Diffusion Model and Diffusion Characteristics on Educational Technology: Case Study of MOOC","authors":"Mengnan Zhu","doi":"10.1145/3545839.3545847","DOIUrl":"https://doi.org/10.1145/3545839.3545847","url":null,"abstract":"With the development of educational informatization, the adoption and diffusion of educational technology have become hot research. As educational technology innovation, the MOOC has opened the \"Internet + Education\" integrated teaching model, and it realized the sharing and diffusion of college educational resources around the world. This paper selects MOOC as the research object and explores the educational technology diffusion, diffusion characteristics, and diffusion process of MOOC based on the innovation diffusion theory. Through the construction of the Bass model, the diffusion process of MOOC in the recent 10 years is analyzed from an objective perspective, and the future diffusion trend of MOOC is predicted.","PeriodicalId":249161,"journal":{"name":"Proceedings of the 2022 5th International Conference on Mathematics and Statistics","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133825158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the periodic table of elements there cannot be elements lighter than hydrogen, but there can be elements heavier than uranium. Presently about 26 transuranic are known. When atoms’ nuclei get heavier, more protons in the nucleus mean more Coulomb force pulling the inner most electrons in, so the electrons orbiting the heavy nuclei have to go faster and faster, reaching speeds that are a substantial fraction of the speed of light. At such high speeds, the electrons become “relativistic,” and the atoms behave differently from what is expected based on their position in the periodic table. Calculations for hydrogen-like atom show that the electrons would have to travel faster than light for atoms with atomic number , which is impossible. This paper questions the validity of incorporating Einstein's relativistic mass well-known formula, , to answer the long standing question of ‘Is there a maximum number of elements corresponding to a theoretical limit for the periodic system?’ We show here that Einstein's most celebrated equation holds if, and only if, the photon is conceived to be mass-ive.
{"title":"Impact of Relativity on the Theoretical Limit for the Periodic System of Elements beyond Uranium","authors":"Talal Al-Ameen, Imad Muhi, Maythem Mahmud","doi":"10.1145/3545839.3545861","DOIUrl":"https://doi.org/10.1145/3545839.3545861","url":null,"abstract":"In the periodic table of elements there cannot be elements lighter than hydrogen, but there can be elements heavier than uranium. Presently about 26 transuranic are known. When atoms’ nuclei get heavier, more protons in the nucleus mean more Coulomb force pulling the inner most electrons in, so the electrons orbiting the heavy nuclei have to go faster and faster, reaching speeds that are a substantial fraction of the speed of light. At such high speeds, the electrons become “relativistic,” and the atoms behave differently from what is expected based on their position in the periodic table. Calculations for hydrogen-like atom show that the electrons would have to travel faster than light for atoms with atomic number , which is impossible. This paper questions the validity of incorporating Einstein's relativistic mass well-known formula, , to answer the long standing question of ‘Is there a maximum number of elements corresponding to a theoretical limit for the periodic system?’ We show here that Einstein's most celebrated equation holds if, and only if, the photon is conceived to be mass-ive.","PeriodicalId":249161,"journal":{"name":"Proceedings of the 2022 5th International Conference on Mathematics and Statistics","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115313818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stochastic differential equations are widely used in atmospheric temperature prediction. This paper based on the established stochastic differential logistic model of global average temperature, it takes Euler's numerical model method to estimate the parameter values and analyze, evaluate the model fitting. The prediction efficiency of the model is determined thereby. Besides, the global average temperature for the next few years is predicted as stated in this paper. Finally, by analyzing the main research variable of global average temperature - environmental capacity, it shows that that if human beings do not get controlled, the global average temperature will continue to increase.
{"title":"Application of Stochastic Differential Equation in Atmospheric Temperature Prediction","authors":"Mingming Xu, Cijun Fang, Desheng Tian","doi":"10.1145/3545839.3545859","DOIUrl":"https://doi.org/10.1145/3545839.3545859","url":null,"abstract":"Stochastic differential equations are widely used in atmospheric temperature prediction. This paper based on the established stochastic differential logistic model of global average temperature, it takes Euler's numerical model method to estimate the parameter values and analyze, evaluate the model fitting. The prediction efficiency of the model is determined thereby. Besides, the global average temperature for the next few years is predicted as stated in this paper. Finally, by analyzing the main research variable of global average temperature - environmental capacity, it shows that that if human beings do not get controlled, the global average temperature will continue to increase.","PeriodicalId":249161,"journal":{"name":"Proceedings of the 2022 5th International Conference on Mathematics and Statistics","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125015893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yunfei Zhou, Hongguang Yang, Bin Cheng, Cheng Wang
In the vacuum heat treatment process, the heat exchange process, temperature field distribution, and cooling rate field distribution inside the vacuum furnace are not easy to observe and measure directly. With the rapid development of numerical simulation technology, the production process of many actual projects can be reproduced on the computer, so that the problems in the project can be analyzed more intuitively and improvements and optimizations can be made.The simulation method generally adopted for the cooling process of vacuum heat treatment only considers the heat exchange process of the cooling gas in the heating chamber, and ignores the integrity of the heat exchange process of the cooling gas, which leads to low authenticity and reliability of the simulation results. The article proposes a cyclic cooling simulation method, and uses the cyclic cooling simulation method to simulate the cooling stage, and compares the simulation results with the experimental results to verify that the cyclic cooling simulation method has higher reliability and calculation accuracy.
{"title":"The finite element simulation and optimization method of the temperature field of vacuum heat treatment based on Fluent","authors":"Yunfei Zhou, Hongguang Yang, Bin Cheng, Cheng Wang","doi":"10.1145/3545839.3545860","DOIUrl":"https://doi.org/10.1145/3545839.3545860","url":null,"abstract":"In the vacuum heat treatment process, the heat exchange process, temperature field distribution, and cooling rate field distribution inside the vacuum furnace are not easy to observe and measure directly. With the rapid development of numerical simulation technology, the production process of many actual projects can be reproduced on the computer, so that the problems in the project can be analyzed more intuitively and improvements and optimizations can be made.The simulation method generally adopted for the cooling process of vacuum heat treatment only considers the heat exchange process of the cooling gas in the heating chamber, and ignores the integrity of the heat exchange process of the cooling gas, which leads to low authenticity and reliability of the simulation results. The article proposes a cyclic cooling simulation method, and uses the cyclic cooling simulation method to simulate the cooling stage, and compares the simulation results with the experimental results to verify that the cyclic cooling simulation method has higher reliability and calculation accuracy.","PeriodicalId":249161,"journal":{"name":"Proceedings of the 2022 5th International Conference on Mathematics and Statistics","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124617078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Coronavirus had been viral and heavily influenced daily lives for more than two years. Two popular procedures to combat the pandemic were general vaccine implantation and limited social contact. We evaluated the effectiveness of these procedures by exploring the trends of vaccination rate, public mobility, and case/death rate at the county level in the mainland United States overtime during 2021. In addition, we investigated how demographic variables such as education and income hindered or promoted vaccination and social contact at the county level. We tested the associations between vaccination rate, public mobility, demographics, and case/death rate using Spearman Correlation tests, Student t-tests, and linear regression. Our findings provide domestic statistical feedback to the anti-epidemic policies and help public health officials make informed decisions in the future.
{"title":"Coronavirus statistics, Google mobility trend, and census demographics in US counties","authors":"Zhou Yang","doi":"10.1145/3545839.3545853","DOIUrl":"https://doi.org/10.1145/3545839.3545853","url":null,"abstract":"The Coronavirus had been viral and heavily influenced daily lives for more than two years. Two popular procedures to combat the pandemic were general vaccine implantation and limited social contact. We evaluated the effectiveness of these procedures by exploring the trends of vaccination rate, public mobility, and case/death rate at the county level in the mainland United States overtime during 2021. In addition, we investigated how demographic variables such as education and income hindered or promoted vaccination and social contact at the county level. We tested the associations between vaccination rate, public mobility, demographics, and case/death rate using Spearman Correlation tests, Student t-tests, and linear regression. Our findings provide domestic statistical feedback to the anti-epidemic policies and help public health officials make informed decisions in the future.","PeriodicalId":249161,"journal":{"name":"Proceedings of the 2022 5th International Conference on Mathematics and Statistics","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125699775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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