The housing crisis in Ireland has rapidly grown in recent years. To make a more significant profit, many landlords are no longer renting out their houses under long-term tenancies but under short-term tenancies. Regul...The housing crisis in Ireland has rapidly grown in recent years. To make a more significant profit, many landlords are no longer renting out their houses under long-term tenancies but under short-term tenancies. Regulating rentals in Rent Pressure Zones with the highest and rising rents is becoming a tricky issue. In this paper, we develop a breach identifier to check short-term rentals located in Rent Pressure Zones with potential breaches only using publicly available data from Airbnb (an online marketplace focused on short-term home-stays) and Irish government websites. First, we use a Residual Neural Network to filter out outdoor landscape photos that negatively impact identifying whether an owner has multiple rentals in a Rent Pressure Zone. Second, a Siamese Neural Network is used to compare the similarity of indoor photos to determine if multiple rental posts correspond to the same residence. Next, we use the Haversine algorithm to locate short-term rentals within a circle centered on the coordinate of a permit. Short-term rentals with a permit will not be restricted. Finally, we improve the occupancy estimation model combined with sentiment analysis, which may provide higher accuracy.展开更多
China's traditional urban land system is established in highly centralized planned economy. This system negates functions of value law and economic law fundamentally,so it is not favorable for establishment of mar...China's traditional urban land system is established in highly centralized planned economy. This system negates functions of value law and economic law fundamentally,so it is not favorable for establishment of market mechanism and development of market economy. This study took Marx's ground rent theory as guidance,combined existing problems of China's land use system,and made analysis on innovation of China's urban land system from property right system,land market and land price.展开更多
Online traffic simulation that feeds from online information to simulate vehicle movement in real-time has recently seen substantial advancement in the development of intelligent transportation systems and urban traff...Online traffic simulation that feeds from online information to simulate vehicle movement in real-time has recently seen substantial advancement in the development of intelligent transportation systems and urban traffic management.It has been a challenging problem due to three aspects:1)The diversity of traffic patterns due to heterogeneous layouts of urban intersections;2)The nature of complex spatiotemporal correlations;3)The requirement of dynamically adjusting the parameters of traffic models in a real-time system.To cater to these challenges,this paper proposes an online traffic simulation framework called automated urban traffic operation simulation via meta-learning(AUTOSIM).In particular,simulation models with various intersection layouts are automatically generated using an open-source simulation tool based on static traffic geometry attributes.Through a meta-learning technique,AUTOSIM enables an automated learning process for dynamic model settings of traffic scenarios featured with different spatiotemporal correlations.Besides,AUTOSIM is capable of adapting traffic model parameters according to dynamic traffic information in real-time by using a meta-learner.Through computational experiments,we demonstrate the effectiveness of the meta-learningbased framework that is capable of providing reliable supports to real-time traffic simulation and dynamic traffic operations.展开更多
It is recognized that a city with a livable environment can bring happiness to residents.In this study,we explored the social media users’emotional states in their current living spaces and found out the relationship...It is recognized that a city with a livable environment can bring happiness to residents.In this study,we explored the social media users’emotional states in their current living spaces and found out the relationship between the social media users’emotions and urban livability.We adopt six urban livability indicators(including education,medical services,public facilities,leisure places,employment,and transportation)to construct city livable indices.Also,the Analytic Hierarchy Process(AHP)spatial statistic method is applied to identify and analyze the different habitable regions of Wuhan City.In terms of citizen’s emotion analysis,we use Long Short-Term Memory(LSTM)neural network to analyze the Weibo text and obtain the Weibo users’sentiment scores.The correlation analysis of residents’emotions and city livability results shows a positive correlation between the livable city areas(i.e.,the area with higher livable ranking indices)and Weibo users’sentiment scores(with a Pearson correlation coefficient of 0.881 and P-Value of 0.004).In other words,people who post Weibo in high livability areas of Wuhan express more positive emotional states.Still,emotion distribution varies in different regions,which is mainly caused by people’s distribution and the diversity of the city’s functional areas.展开更多
As one of the subjects under city-related discussions,locality carries significance in the dimensions of both political and economic space.Western researches have brought about various arguments based on theories of h...As one of the subjects under city-related discussions,locality carries significance in the dimensions of both political and economic space.Western researches have brought about various arguments based on theories of human geography,particularly in the area of urbanization.Taiwan adopts urban renewal as an important approach of revitalizing cities.In view of space theories,multiple political and economic confrontations have occurred during the process of spatial differentiation and reproduction.The analysis on the social phenomenon derived from the urban renewal in Taiwan,China from the perspective of political and economic space,taking into consideration of the correlation between capital and rights,suggests the ongoing development of a new growing pattern of cities under the contention or collaboration among industrial,governmental and academic communities.展开更多
文摘The housing crisis in Ireland has rapidly grown in recent years. To make a more significant profit, many landlords are no longer renting out their houses under long-term tenancies but under short-term tenancies. Regulating rentals in Rent Pressure Zones with the highest and rising rents is becoming a tricky issue. In this paper, we develop a breach identifier to check short-term rentals located in Rent Pressure Zones with potential breaches only using publicly available data from Airbnb (an online marketplace focused on short-term home-stays) and Irish government websites. First, we use a Residual Neural Network to filter out outdoor landscape photos that negatively impact identifying whether an owner has multiple rentals in a Rent Pressure Zone. Second, a Siamese Neural Network is used to compare the similarity of indoor photos to determine if multiple rental posts correspond to the same residence. Next, we use the Haversine algorithm to locate short-term rentals within a circle centered on the coordinate of a permit. Short-term rentals with a permit will not be restricted. Finally, we improve the occupancy estimation model combined with sentiment analysis, which may provide higher accuracy.
文摘China's traditional urban land system is established in highly centralized planned economy. This system negates functions of value law and economic law fundamentally,so it is not favorable for establishment of market mechanism and development of market economy. This study took Marx's ground rent theory as guidance,combined existing problems of China's land use system,and made analysis on innovation of China's urban land system from property right system,land market and land price.
基金supported by the National Natural Science Foundation of China(62173329)。
文摘Online traffic simulation that feeds from online information to simulate vehicle movement in real-time has recently seen substantial advancement in the development of intelligent transportation systems and urban traffic management.It has been a challenging problem due to three aspects:1)The diversity of traffic patterns due to heterogeneous layouts of urban intersections;2)The nature of complex spatiotemporal correlations;3)The requirement of dynamically adjusting the parameters of traffic models in a real-time system.To cater to these challenges,this paper proposes an online traffic simulation framework called automated urban traffic operation simulation via meta-learning(AUTOSIM).In particular,simulation models with various intersection layouts are automatically generated using an open-source simulation tool based on static traffic geometry attributes.Through a meta-learning technique,AUTOSIM enables an automated learning process for dynamic model settings of traffic scenarios featured with different spatiotemporal correlations.Besides,AUTOSIM is capable of adapting traffic model parameters according to dynamic traffic information in real-time by using a meta-learner.Through computational experiments,we demonstrate the effectiveness of the meta-learningbased framework that is capable of providing reliable supports to real-time traffic simulation and dynamic traffic operations.
基金National Key Research and Development Program of China(No.2020YFB2103402)。
文摘It is recognized that a city with a livable environment can bring happiness to residents.In this study,we explored the social media users’emotional states in their current living spaces and found out the relationship between the social media users’emotions and urban livability.We adopt six urban livability indicators(including education,medical services,public facilities,leisure places,employment,and transportation)to construct city livable indices.Also,the Analytic Hierarchy Process(AHP)spatial statistic method is applied to identify and analyze the different habitable regions of Wuhan City.In terms of citizen’s emotion analysis,we use Long Short-Term Memory(LSTM)neural network to analyze the Weibo text and obtain the Weibo users’sentiment scores.The correlation analysis of residents’emotions and city livability results shows a positive correlation between the livable city areas(i.e.,the area with higher livable ranking indices)and Weibo users’sentiment scores(with a Pearson correlation coefficient of 0.881 and P-Value of 0.004).In other words,people who post Weibo in high livability areas of Wuhan express more positive emotional states.Still,emotion distribution varies in different regions,which is mainly caused by people’s distribution and the diversity of the city’s functional areas.
文摘As one of the subjects under city-related discussions,locality carries significance in the dimensions of both political and economic space.Western researches have brought about various arguments based on theories of human geography,particularly in the area of urbanization.Taiwan adopts urban renewal as an important approach of revitalizing cities.In view of space theories,multiple political and economic confrontations have occurred during the process of spatial differentiation and reproduction.The analysis on the social phenomenon derived from the urban renewal in Taiwan,China from the perspective of political and economic space,taking into consideration of the correlation between capital and rights,suggests the ongoing development of a new growing pattern of cities under the contention or collaboration among industrial,governmental and academic communities.
