In this paper,considering the cost of base station,coverage,call quality,and other practical factors,a multi-objective optimal site planning scheme is proposed.Firstly,based on practical needs,mathematical modeling me...In this paper,considering the cost of base station,coverage,call quality,and other practical factors,a multi-objective optimal site planning scheme is proposed.Firstly,based on practical needs,mathematical modeling methods were used to establish mathematical expressions for the three sub-objectives of cost objectives,coverage objectives,and quality objectives.Then,a multi-objective optimization model was established by combining threshold and traffic volume constraints.In order to reduce the time complexity of optimization,a non-dominated sorting genetic algorithm(NSGA)is used to solve the multi-objective optimization problem of site planning.Finally,a strategy for clustering and optimizing weak coverage areas was proposed.In order to avoid redundant neighborhood retrieval during cluster expansion,the Fast Density-Based Spatial Clustering of Applications with Noise(FDBSCAN)clustering method was adopted.With different sub-objectives as the main objectives,this paper obtained the distribution map of weak coverage areas before and after the establishment of new base stations,as well as relevant site planning maps,and provided three planning schemes for different main objectives.The simulation results show that the traffic coverage of the three station planning schemes is above 90%.The change in the main optimization objective will result in a significant difference between the cost of the three solutions and the coverage of weak coverage points.展开更多
The Merchant of Venice is one of the most outstanding comedies of Shakespeare. The story happened in Venice in 16th century. Shylock is a typical character in this play. Shylock was looked down upon and humiliated by ...The Merchant of Venice is one of the most outstanding comedies of Shakespeare. The story happened in Venice in 16th century. Shylock is a typical character in this play. Shylock was looked down upon and humiliated by Christians as a Jew. Shylock, who found everyone in that society was against him, felt him isolated by Christians in Venice. But it is true that as a usurer, shylock was greedy and miserly, he lost kindness and reason; Shylock was oppressed and humiliated as a Jew. This paper focuses on the dual sides of Shylock's character. On one hand he is miserly, unfeeling, vicious and sly; on the other hand, he is oppressed and humiliated.展开更多
Synthetic aperture radar based on the matched filter theory has the ability of obtaining two-di- mensional image of the scattering areas. Nevertheless, the resolution and sidelobe level of SAR imaging is limited by th...Synthetic aperture radar based on the matched filter theory has the ability of obtaining two-di- mensional image of the scattering areas. Nevertheless, the resolution and sidelobe level of SAR imaging is limited by the antenna length and bandwidth of transmitted signal. However, for sparse signals (direct or indirect), sparse imaging methods can break through limitations of the conventional SAR methods. In this paper, we introduce the basic theory of sparse representation and reconstruction, and then analyze several common sparse imaging algorithms: the greed algorithm, the convex optimization algorithm. We apply some of these algorithms into SAR imaging using RadBasedata. The results show the presented method based on sparse construction theory outperforms the conventional SAR method based on MF theory.展开更多
This article addresses the predictability of Bitcoin’s price by examining relationships between Bitcoin and financial and emotional variables such as the Fear and Greed Index(FGI),the American Interest Rate(FED),and ...This article addresses the predictability of Bitcoin’s price by examining relationships between Bitcoin and financial and emotional variables such as the Fear and Greed Index(FGI),the American Interest Rate(FED),and the Stock Market Index(NASDAQ).Through the use of statistical techniques such as the Johansen Cointegration Test and Granger Causality,as well as forecasting models,the study reveals that,despite the notorious volatility of the cryptocurrency market,it is possible to identify consistent behavioral patterns that can be successfully used to predict Bitcoin returns.The approach that combines VAR models and neural networks stands out as an effective tool to assist investors and analysts in making informed decisions in an ever-changing market environment.展开更多
The valuation of cryptocurrencies is important given the increasing significance of this potential asset class.However,most state-of-the-art cryptocurrency valuation methods only focus on one of the fundamental factor...The valuation of cryptocurrencies is important given the increasing significance of this potential asset class.However,most state-of-the-art cryptocurrency valuation methods only focus on one of the fundamental factors or sentiments and use out-of-date data sources.In this study,a robust cryptocurrency valuation method is developed using up-to-date datasets.Using various panel regression models and moving-window regression tests,the impacts of fundamental factors and sentiments in the valuation of cryptocurrencies are explored with data covering from January 1,2009 to April 30,2023.The research shows the importance of sentiments and suggests that the fear and greed index can indicate when to make a cryptocurrency investment,while Google search interest in cryptocurrency is crucial when choosing the appropriate type of cryptocurrency.Moreover,consensus mechanism and initial coin offering have significant effects on cryptocurrencies without stablecoins,while their impacts on cryptocurrencies with stablecoins are insignificant.Other fundamental factors,such as the type of supply and the presence of smart contracts,do not have a significant influence on cryptocurrency.Findings from this study can enhance cryptocurrency marketisation and provide insightful guidance for investors,portfolio managers,and policymakers in assessing the utility level of each cryptocurrency.展开更多
基金The work is supported by Jiangsu Higher Education“Qinglan Project”,an Open Project of Criminal Inspection Laboratory in Key Laboratories of Sichuan Provincial Universities(2023YB03)Major Project of Basic Science(Natural Science)Research in Higher Education Institutions in Jiangsu Province(23KJA520004)+4 种基金Jiangsu Higher Education Philosophy and Social Sciences Research General Project(2023SJYB0467)Action Plan of the National Engineering Research Center for Cybersecurity Level Protection and Security Technology(KJ-24-004)Jiangsu Province Degree and Postgraduate Education and Teaching ReformProject(JGKT24_B036)Digital Forensics Engineering Research Center of the Ministry of Education Open Project(DF20-010)the Youth Fund of Nanjing Railway Vocational and Technical College(Yq220012).
文摘In this paper,considering the cost of base station,coverage,call quality,and other practical factors,a multi-objective optimal site planning scheme is proposed.Firstly,based on practical needs,mathematical modeling methods were used to establish mathematical expressions for the three sub-objectives of cost objectives,coverage objectives,and quality objectives.Then,a multi-objective optimization model was established by combining threshold and traffic volume constraints.In order to reduce the time complexity of optimization,a non-dominated sorting genetic algorithm(NSGA)is used to solve the multi-objective optimization problem of site planning.Finally,a strategy for clustering and optimizing weak coverage areas was proposed.In order to avoid redundant neighborhood retrieval during cluster expansion,the Fast Density-Based Spatial Clustering of Applications with Noise(FDBSCAN)clustering method was adopted.With different sub-objectives as the main objectives,this paper obtained the distribution map of weak coverage areas before and after the establishment of new base stations,as well as relevant site planning maps,and provided three planning schemes for different main objectives.The simulation results show that the traffic coverage of the three station planning schemes is above 90%.The change in the main optimization objective will result in a significant difference between the cost of the three solutions and the coverage of weak coverage points.
文摘The Merchant of Venice is one of the most outstanding comedies of Shakespeare. The story happened in Venice in 16th century. Shylock is a typical character in this play. Shylock was looked down upon and humiliated by Christians as a Jew. Shylock, who found everyone in that society was against him, felt him isolated by Christians in Venice. But it is true that as a usurer, shylock was greedy and miserly, he lost kindness and reason; Shylock was oppressed and humiliated as a Jew. This paper focuses on the dual sides of Shylock's character. On one hand he is miserly, unfeeling, vicious and sly; on the other hand, he is oppressed and humiliated.
文摘Synthetic aperture radar based on the matched filter theory has the ability of obtaining two-di- mensional image of the scattering areas. Nevertheless, the resolution and sidelobe level of SAR imaging is limited by the antenna length and bandwidth of transmitted signal. However, for sparse signals (direct or indirect), sparse imaging methods can break through limitations of the conventional SAR methods. In this paper, we introduce the basic theory of sparse representation and reconstruction, and then analyze several common sparse imaging algorithms: the greed algorithm, the convex optimization algorithm. We apply some of these algorithms into SAR imaging using RadBasedata. The results show the presented method based on sparse construction theory outperforms the conventional SAR method based on MF theory.
文摘This article addresses the predictability of Bitcoin’s price by examining relationships between Bitcoin and financial and emotional variables such as the Fear and Greed Index(FGI),the American Interest Rate(FED),and the Stock Market Index(NASDAQ).Through the use of statistical techniques such as the Johansen Cointegration Test and Granger Causality,as well as forecasting models,the study reveals that,despite the notorious volatility of the cryptocurrency market,it is possible to identify consistent behavioral patterns that can be successfully used to predict Bitcoin returns.The approach that combines VAR models and neural networks stands out as an effective tool to assist investors and analysts in making informed decisions in an ever-changing market environment.
文摘The valuation of cryptocurrencies is important given the increasing significance of this potential asset class.However,most state-of-the-art cryptocurrency valuation methods only focus on one of the fundamental factors or sentiments and use out-of-date data sources.In this study,a robust cryptocurrency valuation method is developed using up-to-date datasets.Using various panel regression models and moving-window regression tests,the impacts of fundamental factors and sentiments in the valuation of cryptocurrencies are explored with data covering from January 1,2009 to April 30,2023.The research shows the importance of sentiments and suggests that the fear and greed index can indicate when to make a cryptocurrency investment,while Google search interest in cryptocurrency is crucial when choosing the appropriate type of cryptocurrency.Moreover,consensus mechanism and initial coin offering have significant effects on cryptocurrencies without stablecoins,while their impacts on cryptocurrencies with stablecoins are insignificant.Other fundamental factors,such as the type of supply and the presence of smart contracts,do not have a significant influence on cryptocurrency.Findings from this study can enhance cryptocurrency marketisation and provide insightful guidance for investors,portfolio managers,and policymakers in assessing the utility level of each cryptocurrency.
