Late-night noise hazards and the Tokyo Metropolitan Government's countermeasures in the 1960s

In 1960s Tokyo, late-night noise became a source of annoyance for urban-dwellers in residential areas. The problem was primarily due to young people who congregated around small food establishments eating and drinking. The situation led to the Tokyo Metropolitan Government to attempt to remove such small businesses through the 1969 Environmental Pollution Prevention Ordinance. However, the section of the ordinance dealing with late-night noise hazards was diluted by the political parties, who supported the interests of such businesses, hence failing to satisfy local residents who were victims of the problem.

The city in the constitutional imagination

This article reviews Ran Hirschl’s City, State, a study of ‘the great constitutional silence concerning one of the most significant phenomena of our time: urban agglomeration and the rise of megacities’ and which maintains that the solution to contemporary urban problems crucially depends on a ‘constitutional emancipation’ of the city. The article argues that Hirschl is unable to deliver on his major claim. Launching his thesis on a skewed account of the development of the political role of the city, a one-sided presentation of the constitutional order of the modern state, and a failure to appreciate the impact of urbanization on the city’s standing as a unit of government, Hirschl ignores the work of public lawyers on the challenges of metropolitan government and argues, unconvincingly, that these challenges can be resolved once we turn to the abstractions of constitutional theory.

Estimation of the Original Location of Haechi (Haetae) Statues in Front of Gwanghwamun Gate Using Archival Photos from Early 1900s and Newly Taken Photos by Image Analysis

Gwanghwamun Gate of Gyeongbokgung Palace was dismantled and relocated during the Japanese colonial period, destroyed during the Korean War, reconstructed with reinforced concrete in 1968, and finally erected at its present location in 2010. A pair of Haechi statues located in front of Gwanghwamun was dismantled and relocated several times, and the statues have yet to be returned precisely to their original positions. This study assesses the historical accuracy of their current placement under the Gwanghwamun Square Restructuring Project of the Seoul Metropolitan Government and the Cultural Heritage Administration based on archival photos from the early 1900s, and proposes a method to estimate the original positions of the Haechi through image analysis of contemporary photographs and recent digital camera photos. We estimated the original position of the Haechi before the Japanese colonial period by identifying the shooting location of the archival photo and reproducing contemporary photographs by calculating the angle and distance to the Haechi from the shooting location. The leftmost and rightmost Haechi were originally located about 9.6 m to the east and 7.4 m to the north and about 1.9 m to the west and 8.0 m to the north, respectively, of their current location indicators. As the first attempt to determine the original location of a building and its accessories using archival photos, this study launches a new scientific methodology for the restoration of cultural properties.

Development of Heatwave Probability Prediction Model Based on Recurrent Neural Network: A Case of Seoul Metropolitan Government

Recently, the incidence of heat waves has increased due to climate change, and the resultant mortalities and socio-economic damage are also increasing in Korea. Hence, emphasis has been placed on research examining heatwaves and their effects. Predicting the probability of heatwave in advance is very important from the perspective of disaster risk management; however, related studies have been insufficient so far. Therefore, in this study, the probability of future heatwave onset was predicted using daily scaled past weather data for Seoul Metropolitan Government. For the analysis, models based on recurrent neural networks (RNN, LSTM, GRU) were used, which are suitable for analyzing time-series data. Upon evaluating the performance of the GRU model, which was selected as the optimized model, no overfitting problem was observed. The prediction accuracy of the model was high as it demonstrated a reproduction of 78% and 86% of actual heatwave days during the validation and test process, respectively. Therefore, this model can be used by each local government to coordinate an efficient response to heat waves.

Zone-Agnostic Greedy Taxi Dispatch Algorithm Based on Contextual Matching Matrix for Efficient Maximization of Revenue and Profit

This paper addresses the taxi fleet dispatch problem, which is critical for many transport service platforms such as Uber, Lyft, and Didi Chuxing. We focus on maximizing the revenue and profit a taxi platform can generate through the dispatch approaches designed with various criteria. We consider determining the proportion of taxi fleets to different destination zones given the expected rewards from the future states following the distribution decisions learned through reinforcement learning (RL) algorithms. We also take into account more straightforward greedy algorithms that look ahead fewer decision time steps in the future. Our dispatch decision algorithms commonly leverage contextual information and heuristics using a data structure called Contextual Matching Matrix (CMM). The key contribution of our paper is the insight into the trade-off between different design criteria. Primarily, through the evaluation with actual taxi operation data offered by Seoul Metropolitan Government, we challenge the natural expectation that the RL-based approaches yield the best result by showing that a lightweight greedy algorithm can have a competitive advantage. Moreover, we break the norm of dissecting the service area into sub-zones and show that matching passengers beyond arbitrary boundaries generates significantly higher operating income and profit.