Human mobility and infection from Covid19 in the Osaka metropolitan area npj Urban Sustainability

Human mobility and infection from Covid-19 in the Osaka metropolitan area

It is considered that controlling human movement is effective as a measure to prevent the expansion of COVID-19 pandemic. This study was to clarify the type of human movement that influenced the number of COVID-19 patients in the medium-term epidemic of COVID-19 pandemic in the Osaka metropolitan area. The method used in this study is an analysis of the statistical relationship between the change in the movement of people two weeks later and the total number of patients in COVID-19. In conclusion, it was indispensable to reduce the degree of movement of people at grocery stores and pharmacies t o-5 to 5 %, and to reduce the movement of the park t o-20 % or more. The most important discovery for the sustainability of the city is that urban transportation is not a source of infection. Therefore, if the hygiene management process has been implemented in Osaka in cities around the world, the government may encourage the government to return to local communities.

Non-compulsory measures sufficiently reduced human mobility in Tokyo during the COVID-19 epidemic

Paper release October 22, 2020

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Paper release July 10, 2023

Impact of urbanisation and environmental factors on spatial distribution of COVID-19 cases during the early phase of epidemic in Singapore

Public release June 13, 2022 COVID-19 As a measure to prevent the expansion of pandemic, it is considered that it is effective to control human movement. This study was to clarify the type of human movement that influenced the number of COVID-19 patients in the medium-term epidemic of COVID-19 pandemic in the Osaka metropolitan area. The method used in this study is an analysis of the statistical relationship between the change in the movement of people two weeks later and the total number of patients in COVID-19. In conclusion, it was indispensable to reduce the degree of movement of people at grocery stores and pharmacies t o-5 to 5 %, and to reduce the movement of the park t o-20 % or more. The most important discovery for the sustainability of the city is that urban transportation is not a source of infection. Therefore, if the hygiene management process has been implemented in Osaka in cities around the world, the government may encourage the government to return to local communities.

Introduction

Paper release October 22, 2020

Paper release July 10, 2023

Published dissertation June 13, 2022 COVID-19 COVID-19 As a measure to prevent the expansion of pandemic, it is considered that it is effective to control human movement. This study was to clarify the type of human movement that influenced the number of COVID-19 patients in the medium-term epidemic of COVID-19 pandemic in the Osaka metropolitan area. The method used in this study is an analysis of the statistical relationship between the change in the movement of people two weeks later and the total number of patients in COVID-19. In conclusion, it was indispensable to reduce the degree of movement of people at grocery stores and pharmacies t o-5 to 5 %, and to reduce the movement of the park t o-20 % or more. The most important discovery for the sustainability of the city is that urban transportation is not a source of infection. Therefore, if the hygiene management process has been implemented in Osaka in cities around the world, the government may encourage the government to return to local communities.

Paper release October 22, 2020

Paper release July 10, 2023

Paper release June 13, 2022

The COVID-19 pandemic has been reported to have had a positive impact on urban sustainability in the short term1. However, the pandemic may not continue to have a positive impact on urban sustainability in the medium term. For example, several door locks caused changes in mobility, especially public transportation, due to concerns about COVID-19 infection2. However, modal shifts from public transportation to automobiles have a negative impact on reducing carbon dioxide emissions3. Controlling people's mobility is considered an effective non-pharmacological intervention to prevent the global spread of the COVID-19 pandemic and has been implemented in, for example, the United States, the EU, and China4, 5, 6. To control people's mobility, states of emergency have been declared multiple times during the COVID-19 pandemic. For example, the Japanese government issued multiple states of emergency in Osaka Prefecture7. During these emergency declaration periods, the COVID-19 Infection Control Subcommittee in Japan requested residents to reduce their mobility by 50%8. During the first state of emergency, the request led to a 50% reduction in residential area in suburban cities in the Osaka metropolitan area as residents changed their transportation methods to walking and cycling 9, 10, 11 . A decrease in human mobility was also reported in Tokyo during the same first state of emergency 12 . However, some studies suggest that the effect of suppressing the spread of human mobility is different from the effect of suppressing the spread of resident mobility.

In this study, we investigate the following research question: Where should human mobility be controlled to reduce the number of COVID-19 cases? COVID-19 transmission is influenced by many factors, such as population density, temperature, and vaccination rate 16 . However, human mobility has been found to affect COVID-19 transmission more strongly than other factors 17 . Moreover, human mobility is a factor that government policies can intervene in. Currently, COVID-19 transmission is strongly influenced by vaccination rate 18 . However, some people cannot be vaccinated for religious or health reasons. Moreover, it will be difficult to develop a vaccine immediately for future new infectious diseases. Therefore, controlling human movement is the most fundamental measure for non-pharmaceutical interventions against future infectious diseases. For this reason, it is necessary to focus on human movement in this study.

Closing schools and companies has been reported to be effective in controlling people's movements 9, 10, 11. In addition, many prefectures in Japan have requested restaurants to close by 8 p. m. and refrain from serving alcohol 7. However, in order to prevent the spread of the COVID-19 pandemic, it is necessary to consider restrictions on places that have not been considered before. In addition, to maintain socio-economic activities, it is also necessary to consider removing restrictions in places where infection is unlikely to occur. Therefore, what kind of people's movements contribute to how policymakers formulate policies to suppress the spread of infection for the sustainability of cities.

Results

Changes in human mobility

This study aimed to clarify the types of human movements that influenced the number of COVID-19 patients during the mid-pandemic of COVID-19 in the Osaka metropolitan area. The method used in this study was the analysis of the statistical relationship between changes in people's movements after 2 weeks and the total number of COVID-19 patients. Using data from Google Community Mobility Reports, the types of human movement were classified into six categories: retail/recreation, groceries/pharmacies, parks, transportation stations, workplaces, and residential areas. 19 These types of human movement are analyzed based on the relative changes in the number of visitors to the six types of places. Random forest analysis is applied to determine this statistical relationship.

The Osaka metropolitan area from March 1, 2020 to September 30, 2021 was selected as a case study. In the middle period, in the Osaka metropolitan area, the number of COVID-19 patients experienced five waves while repeatedly increasing and decreasing. During this time, vaccination began for medical workers in February 2021 and for the elderly and adults in April 2021. As a result, the fourth emergency declaration was lifted on September 30, 2021 in the Osaka metropolitan area. In this study, as shown in Figure 1, the Osaka area consists of three prefectures in Osaka, Kyoto, and Hyogo prefectures. The satellite map in Fig. 1 is compliant with copyright 20. Unlike other metropolitan areas, there are three central areas in the Osaka metropolitan area: Umeda in Osaka, Karasuma in Kyoto, and Kobe in Hyogo prefectures. These areas were connected by multiple railways and highways, so the number of infected people was rapidly increasing. In the early COVID-19 pandemic, it turned out that the size of the city and the number of COVID-19 infected people are correlated 21. For this reason, COVID-19 measures were often discussed by the governor of the three prefectures and were often implemented jointly. For example, the three prefectures jointly requested the Japanese government to declare an emergency. In addition, the period of an emergency declaration is the same for the three prefectures. Therefore, it is appropriate to analyze these three prefectures as the Osaka metropolitan area.

Figure 1: Map of the Osaka metropolitan area.

In this study, the three prefectures of Osaka, Kyoto and Hyogo were set to the Osaka metropolitan area. (A) in Fig. 1 shows the location of the Osaka metropolitan area in East Asia, and (b) is the location of the three prefectures included in the Osaka metropolitan area. The Osaka metropolitan area has three central urban areas, with multiple railways running. The satellite map conforms to copyright 20. The Osaka metropolitan area from March 1, 2020 to September 30, 2021 was selected as a case study. In the middle period, in the Osaka metropolitan area, the number of COVID-19 patients experienced five waves while repeatedly increasing and decreasing. During this time, vaccination began for medical workers in February 2021 and for the elderly and adults in April 2021. As a result, the fourth emergency declaration was lifted on September 30, 2021 in the Osaka metropolitan area. In this study, as shown in Figure 1, the Osaka area consists of three prefectures in Osaka, Kyoto, and Hyogo prefectures. The satellite map in Fig. 1 is compliant with copyright 20. Unlike other metropolitan areas, there are three central areas in the Osaka metropolitan area: Umeda in Osaka, Karasuma in Kyoto, and Kobe in Hyogo prefectures. These areas were connected by multiple railways and highways, so the number of infected people was rapidly increasing. In the early COVID-19 pandemic, it turned out that the size of the city and the number of COVID-19 infected people are correlated 21. For this reason, COVID-19 measures were often discussed by the governor of the three prefectures and were often implemented jointly. For example, the three prefectures jointly requested the Japanese government to declare an emergency. In addition, the period of an emergency declaration is the same for the three prefectures. Therefore, it is appropriate to analyze these three prefectures as the Osaka metropolitan area.

Change in the Number of COVID-19 Cases

Figure 1: Map of the Osaka metropolitan area.

In this study, the three prefectures of Osaka, Kyoto and Hyogo were set to the Osaka metropolitan area. (A) in Fig. 1 shows the location of the Osaka metropolitan area in East Asia, and (b) is the location of the three prefectures included in the Osaka metropolitan area. The Osaka metropolitan area has three central urban areas, with multiple railways running. The satellite map conforms to copyright 20. The Osaka metropolitan area from March 1, 2020 to September 30, 2021 was selected as a case study. In the middle period, in the Osaka metropolitan area, the number of COVID-19 patients experienced five waves while repeatedly increasing and decreasing. During this time, vaccination began for medical workers in February 2021 and for the elderly and adults in April 2021. As a result, the fourth emergency declaration was lifted on September 30, 2021 in the Osaka metropolitan area. In this study, as shown in Figure 1, the Osaka area consists of three prefectures in Osaka, Kyoto, and Hyogo prefectures. The satellite map in Fig. 1 is compliant with copyright 20. Unlike other metropolitan areas, there are three central areas in the Osaka metropolitan area: Umeda in Osaka, Karasuma in Kyoto, and Kobe in Hyogo prefectures. These areas were connected by multiple railways and highways, so the number of infected people was rapidly increasing. In the early COVID-19 pandemic, it turned out that the size of the city and the number of COVID-19 infected people are correlated 21. For this reason, COVID-19 measures were often discussed by the governor of the three prefectures and were often implemented jointly. For example, the three prefectures jointly requested the Japanese government to declare an emergency. In addition, the period of an emergency declaration is the same for the three prefectures. Therefore, it is appropriate to analyze these three prefectures as the Osaka metropolitan area.

Figure 1: Map of the Osaka metropolitan area.

Human mobility types that impact the number of COVID-19 cases

Many studies of human mobility have used mobile phone data to predict SARS-CoV-2 case numbers. Restaurants, fitness centers, cafes, bars, and hotels have been found to be high-risk locations for infection. 22 In Japan, human mobility in nightlife areas in downtown areas has been found to be higher risk than residences and workplaces. 23 Prefectures also often consider COVID-19 countermeasures based on human mobility in transportation stations. 24 For example, Osaka Prefecture has issued a warning when human mobility increases at terminal stations. 24 Similar to this study, random forest analysis using data from Google Community Mobility Reports shows that important mobility areas are retail/recreation, grocery/pharmacy, and transfer stations in the EU case from March to April 2020. 25 Moreover, in Germany from February to July 2020, factors associated with case numbers include increased human mobility in grocery/pharmacy and decreased mobility in workplaces and retail/recreation. 26 In terms of personal mobility, Portugal saw a decline in workplace and transport mobility during the pandemic27. The results showed that workplace closures were almost as effective as stay-at-home orders in terms of social distancing policies28. Japan had one of the largest declines in mobility in the world29. In addition to workplace mobility, park mobility has also been noted.

The novelty of this study based on previous studies is that it clarified the types of people’s mobility during the mid-stage of the COVID-19 pandemic. In Japan, the state of emergency was called a “soft lockdown” because the Japanese government did not restrict individual behavior. 31 For example, Osaka Prefecture requested railway companies to conduct temperature checks at major terminal stations and advance the last train time. 32 Based on the prefecture’s request, railway companies also decided to keep the number of daytime trains the same as before the pandemic, even though the number of passengers had decreased significantly. 33 Some railway companies in Osaka also provided incentives to people who rode trains when the number of passengers was low. 34 These hygiene controls reduced the mobility density at transfer stations. Therefore, even under the state of emergency, most citizens were able to go out at least occasionally. Therefore, there may be diversity in the relationship between mobility types and COVID-19 cases. This result will help policymakers plan effective mobility controls for urban sustainability. However, it is difficult to obtain accurate results for the mid-term COVID-19 pandemic13, 14, 15 because the number of COVID-19 cases and people's movements may have a nonlinear relationship due to factors such as policy effects and new influenza. Figure 2 shows the daily changes in human mobility in Osaka, Kyoto, and Hyogo prefectures during the middle of the COVID-19 pandemic. Figure 2 shows the spline curve and confidence interval. The smoothing parameter λ of the spline curve was set to 0. 001. In addition, Figure 2 shows the state of emergency declaration period. As a result, similar changes were observed in Osaka, Kyoto, and Hyogo prefectures.

Figure 2: Changes in human mobility from March 2020 to September 2021.

The types of human mobility are retail and entertainment (a), grocery stores and pharmacies (b), parks (c), transportation stations (d), workplaces (e), and residential areas (f). The green points and lines are data for Osaka Prefecture, the red points and lines are data for Kyoto Prefecture, and the blue points and lines are data for Hyogo Prefecture.

Figure 2 shows that human mobility varies by six types. After March 2020, all types of human mobility except residential mobility decrease. This suggests that more people stayed home even without stay-at-home orders. When residential mobility increases, other mobility decreases. The state of emergency caused a decrease in mobility for transportation, retail, and recreational purposes. In addition, during vacation periods such as summer vacation and the New Year holidays, mobility for workplaces decreased dramatically. Movement for grocery and pharmacy purposes changed slightly during the state of emergency, but remained at almost 0%. Movement for parks increased during the first state of emergency, but then decreased.

Figure 3 shows the daily change in the number of SARS-CoV-2 infected people in Osaka, Kyoto, and Hyogo prefectures. Figure 3 shows the spline curve and confidence interval. The smoothing parameter λ for the spline curve was set to 0. 001. Figure 3 also shows the period of the state of emergency.

Discussion

Figure 3: Changes in the number of COVID-19 patients.

The green points and lines are data for Osaka Prefecture, the red points and lines are data for Kyoto Prefecture, and the blue points and lines are data for Hyogo Prefecture.

Figure 3 shows that in Osaka, Kyoto, and Hyogo prefectures, COVID-19 infected people have increased or decreased with five waves from February 2020 to December 2021. The first wave is April 2020, the second wave is from July 2020 to September 2020, the third wave is from 2020 to February 2021, and the fourth wave is March 2021 to June. The fifth wave is from July to September 2021. The number of infected people has gradually increased from the first wave to the fourth wave. The first, third, fourth and fifth waves were issued an emergency declaration. The emergency declaration has effectively reduced the number of infected COVID-19.

Table 1 and 4 shows the type of movement of people who influenced the total number of patients in Osaka, Kyoto, and Hyogo two weeks later. Statistical analysis used the Random Forest Law. Table 1 shows the main effects of each prefecture and all effects. Figure 4 shows the importance of variables in Osaka, Kyoto, and Hyogo prefectures. As shown in Table 1, the R 2 score of all models is 0. 7 or more, indicating that the accuracy is high. Consider the results separately by prefecture.

Table 1 Temporary effects and total effects for each prefecture

Fig. 4 The importance of variables by prefecture

The importance of variables is evaluated by the subordinate-re-specimen input, which is a factor value built from a recent approach using a recent approach. Fig. 4 shows the importance of variables in Osaka Prefecture, (b), and (c) in Hyogo Prefecture.

Methods

Human mobility data

In Osaka Prefecture, the R 2 score is 0. 777, indicating that the model is highly accurate. The total effect is high for people in the food shop / pharmacy (total effect = 0. 437), park (total effect = 0. 368), workplace (total effect = 0. 253), and residential area (total effect = 0. 234). Two weeks later, the total number of patients in COVID-19 gradually decreased due to the decrease in the movement of food stores / pharmacies to decrease by about 5 to-5 %. In addition, the movement of people in the park has increased fro m-20 % t o-20 %, and the number of COVID-19 has decreased. In addition, it was found that the movement of people at the transfer station was less effective (total effect = 0. 102). Figure 3 shows that in Osaka, Kyoto, and Hyogo prefectures, COVID-19 infected people have increased or decreased with five waves from February 2020 to December 2021. The first wave is April 2020, the second wave is from July 2020 to September 2020, the third wave is from 2020 to February 2021, and the fourth wave is March 2021 to June. The fifth wave is from July to September 2021. The number of infected people has gradually increased from the first wave to the fourth wave. The first, third, fourth and fifth waves were issued an emergency declaration. The emergency declaration has effectively reduced the number of infected COVID-19.

Number of COVID-19 cases data

Table 1 Temporary effects and total effects for each prefecture

Statistical analysis

Fig. 4 The importance of variables by prefecture

In Osaka Prefecture, the R 2 score is 0. 777, indicating that the model is highly accurate. The total effect is high for people in the food shop / pharmacy (total effect = 0. 437), park (total effect = 0. 368), workplace (total effect = 0. 253), and residential area (total effect = 0. 234). Two weeks later, the total number of patients in COVID-19 gradually decreased due to the decrease in the movement of food stores / pharmacies to decrease by about 5 to-5 %. In addition, the movement of people in the park has increased fro m-20 % t o-20 %, and the number of COVID-19 has decreased. In addition, it was found that the movement of people at the transfer station was less effective (total effect = 0. 102). Figure 3 shows that in Osaka, Kyoto, and Hyogo prefectures, COVID-19 infected people have increased or decreased with five waves from February 2020 to December 2021. The first wave is April 2020, the second wave is from July 2020 to September 2020, the third wave is from 2020 to February 2021, and the fourth wave is March 2021 to June. The fifth wave is from July to September 2021. The number of infected people has gradually increased from the first wave to the fourth wave. The first, third, fourth and fifth waves were issued an emergency declaration. The emergency declaration has effectively reduced the number of infected COVID-19.

Data availability

Table 1 Temporary effects and total effects for each prefecture

References

Fig. 4 The importance of variables by prefecture
The importance of variables is evaluated by the subordinate-re-specimen input, which is a factor value built from a recent approach using a recent approach. Fig. 4 shows the importance of variables in Osaka Prefecture, (b), and (c) in Hyogo Prefecture.
In Osaka Prefecture, the R 2 score is 0. 777, indicating that the model is highly accurate. The total effect is high for people in the food shop / pharmacy (total effect = 0. 437), park (total effect = 0. 368), workplace (total effect = 0. 253), and residential area (total effect = 0. 234). Two weeks later, the total number of patients in COVID-19 gradually decreased due to the decrease in the movement of food stores / pharmacies to decrease by about 5 to-5 %. In addition, the movement of people in the park has increased fro m-20 % t o-20 %, and the number of COVID-19 has decreased. In addition, it was found that the movement of people at the transfer station was less effective (total effect = 0. 102).
In Kyoto Prefecture, the R 2 score is 0. 821, indicating that the accuracy of the model is high. In addition, the movement of people in food stores and pharmacies (total effects 0. 418), park (total effects 0. 363), and residential areas (total effects 0. 216) showed high effects. Two weeks after COVID-19, the total number of patients gradually decreased by increasing the movement of food stores / pharmacies by abou t-5 to 5 %. In addition, the movement of people in the park increased fro m-20 % to 50 %, and the number of COVID-19 has decreased. In addition, it was found that the transfer of the transfer station was low (total effect = 0. 148).
In Hyogo Prefecture, the R 2 score was 0. 775, indicating that the accuracy of the model was high. In the food store / pharmacy (total effect = 0. 495), park (total effect = 0. 303), and residential areas (total effect = 0. 245), people's movement was high. Two weeks after COVID-19, the total number of occurrence gradually decreased by increasing the degree of movement of food stores / pharmacies by abou t-5 to 5 %. In addition, the movement of people in the park increased fro m-50 % to 10 %, and the number of COVID-19 has decreased. In addition, it was found that the movement of people at the transfer station was less effective (total effect = 0. 146). Kyoto Prefecture has a R 2 score of 0. 821, indicating that the accuracy of the model is high. In addition, the movement of people in food stores and pharmacies (total effects 0. 418), park (total effects 0. 363), and residential areas (total effects 0. 216) showed high effects. Two weeks after COVID-19, the total number of patients gradually decreased by increasing the movement of food stores / pharmacies by abou t-5 to 5 %. In addition, the movement of people in the park increased fro m-20 % to 50 %, and the number of COVID-19 has decreased. In addition, it was found that the transfer of the transfer station was low (total effect = 0. 148).
In Hyogo Prefecture, the R 2 score was 0. 775, indicating that the accuracy of the model was high. In the food store / pharmacy (total effect = 0. 495), park (total effect = 0. 303), and residential areas (total effect = 0. 245), people's movement was high. Two weeks after COVID-19, the total number of occurrence gradually decreased by increasing the degree of movement of food stores / pharmacies by abou t-5 to 5 %. In addition, the movement of people in the park increased fro m-50 % to 10 %, and the number of COVID-19 has decreased. In addition, it was found that the movement of people at the transfer station was less effective (total effect = 0. 146). In Kyoto Prefecture, the R 2 score is 0. 821, indicating that the accuracy of the model is high. In addition, the movement of people in food stores and pharmacies (total effects 0. 418), park (total effects 0. 363), and residential areas (total effects 0. 216) showed high effects. Two weeks after COVID-19, the total number of patients gradually decreased by increasing the movement of food stores / pharmacies by abou t-5 to 5 %. In addition, the movement of people in the park increased fro m-20 % to 50 %, and the number of COVID-19 has decreased. In addition, it was found that the transfer of the transfer station was low (total effect = 0. 148).
In Hyogo Prefecture, the R 2 score was 0. 775, indicating that the accuracy of the model was high. In the food store / pharmacy (total effect = 0. 495), park (total effect = 0. 303), and residential areas (total effect = 0. 245), people's movement was high. Two weeks after COVID-19, the total number of occurrence gradually decreased by increasing the degree of movement of food stores / pharmacies by abou t-5 to 5 %. In addition, the movement of people in the park increased fro m-50 % to 10 %, and the number of COVID-19 has decreased. In addition, it was found that the movement of people at the transfer station was less effective (total effect = 0. 146).
In conclusion, the analysis results have shown that it is essential to contro l-5 to 5 % for the movement of grocery stores / pharmacies, and the park movement to more tha n-20 %. This knowledge is important because the number of SARS-COV-2 infected people can be reduced by controlling human movement. In order to suppress the movement of food stores and pharmacies, the government needs to actively encourage residents on online shopping and distribute the time of food stores and pharmacies. The target value to suppress people's movement i s-5 to 5 %. This value means that the movement of food and pharmacies needs to be controlled in the same way as before the pandemic. Looking at Figure 2, it can be seen that there is little effect on the movement of food/ pharmacies due to pandemic. However, all generations go to grocery stores / pharmacies every day. In addition, food stores and pharmacies always have social contact. Therefore, the movement of food stores and pharmacies has a strong effect on the number of patients in COVID-19, although the pandemic is small. It is necessary to control the movement of food stores and pharmacies so that they do not increase or decrease too much. In fact, when the delta type became popular in the Osaka metropolitan area, group infections at grocery stores and department stores frequently occurred. In the past, the Japanese government did not restrict the necessary shopping to maintain daily life, even during the emergency declaration period. This study suggests the following: In conclusion, the conclusion has shown that this analysis is indispensable to contro l-5 to 5 % for people at grocery stores / pharmacies, and to move in the park to more tha n-20 %. This knowledge is important because the number of SARS-COV-2 infected people can be reduced by controlling human movement. In order to suppress the movement of food stores and pharmacies, the government needs to actively encourage residents on online shopping and distribute the time of food stores and pharmacies. The target value to suppress people's movement i s-5 to 5 %. This value means that the movement of food and pharmacies needs to be controlled in the same way as before the pandemic. Looking at Figure 2, it can be seen that there is little effect on the movement of food/ pharmacies due to pandemic. However, all generations go to grocery stores / pharmacies every day. In addition, food stores and pharmacies always have social contact. Therefore, the movement of food stores and pharmacies has a strong effect on the number of patients in COVID-19, although the pandemic is small. It is necessary to control the movement of food stores and pharmacies so that they do not increase or decrease too much. In fact, when the delta type became popular in the Osaka metropolitan area, group infections at grocery stores and department stores frequently occurred. In the past, the Japanese government did not restrict the necessary shopping to maintain daily life, even during the emergency declaration period. This study suggests the following: In conclusion, the analysis results have shown that it is essential to contro l-5 to 5 % for the movement of grocery stores / pharmacies, and the park movement to more tha n-20 %. This knowledge is important because the number of SARS-COV-2 infected people can be reduced by controlling human movement. In order to suppress the movement of food stores and pharmacies, the government needs to actively encourage residents on online shopping and distribute the time of food stores and pharmacies. The target value to suppress people's movement i s-5 to 5 %. This value means that the movement of food and pharmacies needs to be controlled in the same way as before the pandemic. Looking at Figure 2, it can be seen that there is little effect on the movement of food/ pharmacies due to pandemic. However, all generations go to grocery stores / pharmacies every day. In addition, food stores and pharmacies always have social contact. Therefore, the movement of food stores and pharmacies has a strong effect on the number of patients in COVID-19, although the pandemic is small. It is necessary to control the movement of food stores and pharmacies so that they do not increase or decrease too much. In fact, when the delta type became popular in the Osaka metropolitan area, group infections at grocery stores and department stores frequently occurred. In the past, the Japanese government did not restrict the necessary shopping to maintain daily life, even during the emergency declaration period. This study suggests the following:
We found that the movement of people in parks also affects the number of infected people. As previous studies 25, 26 have shown, increasing the movement of people in parks contributes to a decrease in the number of infected people. This finding suggests that increasing the movement of people in parks reduces the number of infected people. In other words, when a state of emergency is declared, instead of restricting the movement of people at grocery stores and pharmacies, parks can be actively used.
The most important finding for urban sustainability is that urban transportation is not a source of infection. The movement of people at transportation stations has been used as a reference for policy making 24. Therefore, governments of cities around the world may be able to encourage their communities to return to transportation travel if they can follow a sanitation process such as that implemented in Osaka. Such a sanitation process would be to maintain the number of trains departing during the day even if the number of passengers is significantly reduced 33. Also, effective sanitation management would be to give incentives to people to ride trains during times when there are fewer passengers. Such sanitation management reduced the density of people moving at transfer stations 34. Based on these results, the government can consider abolishing restrictions at transfer stations where infections are less likely to occur. If more people use public transportation, air pollution such as carbon dioxide emissions can be reduced.
It also became clear that the third most influential factor, "people's movement," needs to be considered in accordance with the characteristics of each prefecture. For example, in the case of Osaka Prefecture, the number of infected people can be reduced by allowing people to go to work by setting the movement of people at work to 0%. This result suggests that it is better for the government to prevent work-related activities such as shopping rather than preventing people from going to work.
Currently, many people can be vaccinated in many countries. On the other hand, new variants of COVID-19 are constantly occurring. Therefore, as the number of infected people is regularly increased or decreased, the possibility of pandemic is unlikely to end. Human movement control may continue to be the most effective way to intervene in the future. However, unlike the early pandemic, there is no need to stop all human movements by blocking. The results of this study indicate that controlling the movement of a specific type of person can be expected to have a greater effect. For example, it is possible to reduce the number of opportunities to go to grocery stores and pharmacies, or to inform them of safety when going to parks and transportation stations. This discovery is important and important to maintain social and economic activities in pandemic after COVID-19.
However, this change may adversely affect the sustainability of the city during the medium-term Covid-19 pandemic. Air pollution decreased by 38 due to restrictions on human movement. If the government simply activates human movement, there is a possibility that carbon dioxide emissions due to car traffic will increase 39. Therefore, the government needs to combine several policies, such as working from home, online shopping, and active use of public transportation. For example, in order to realize a new lifestyle using public transportation, it is important to design an eas y-t o-walk area. The ease of walking is expected to contribute to the health of the inhabitants 41, the ecological footprint 42, and the future population of 43. The mayor of Paris, Anne Idalgo, advocates the realization of a city for 15 minutes by 2024, and has moved to easy-to-walk areas where people can live without using cars since the COVID-19 Pandemic era. 44. These policies could contribute to the sustainability of cities after COVID-19 pandemic for planners and policy proprieters. Currently, many people can be vaccinated in many countries. On the other hand, new variants of COVID-19 are constantly occurring. Therefore, as the number of infected people is regularly increased or decreased, the possibility of pandemic is unlikely to end. Human movement control may continue to be the most effective way to intervene in the future. However, unlike the early pandemic, there is no need to stop all human movements by blocking. The results of this study indicate that controlling the movement of a specific type of person can be expected to have a greater effect. For example, it is possible to reduce the number of opportunities to go to grocery stores and pharmacies, or to inform them of safety when going to parks and transportation stations. This discovery is important and important to maintain social and economic activities in pandemic after COVID-19.
However, this change may adversely affect the sustainability of the city during the medium-term Covid-19 pandemic. Air pollution decreased by 38 due to restrictions on human movement. If the government simply activates human movement, there is a possibility that carbon dioxide emissions due to car traffic will increase 39. Therefore, the government needs to combine several policies, such as working from home, online shopping, and active use of public transportation. For example, in order to realize a new lifestyle using public transportation, it is important to design an eas y-t o-walk area. The ease of walking is expected to contribute to the health of the inhabitants 41, the ecological footprint 42, and the future population of 43. The mayor of Paris, Anne Idalgo, advocates the realization of a city for 15 minutes by 2024, and has moved to easy-to-walk areas where people can live without using cars since the COVID-19 Pandemic era. 44. These policies could contribute to the sustainability of cities after COVID-19 pandemic for planners and policy proprieters. Currently, many people can be vaccinated in many countries. On the other hand, new variants of COVID-19 are constantly occurring. Therefore, as the number of infected people is regularly increased or decreased, the possibility of pandemic is unlikely to end. Human movement control may continue to be the most effective way to intervene in the future. However, unlike the early pandemic, there is no need to stop all human movements by blocking. The results of this study indicate that controlling the movement of a specific type of person can be expected to have a greater effect. For example, it is possible to reduce the number of opportunities to go to grocery stores and pharmacies, or to inform them of safety when going to parks and transportation stations. This discovery is important and important to maintain social and economic activities in pandemic after COVID-19.
However, this change may adversely affect the sustainability of the city during the medium-term Covid-19 pandemic. Air pollution decreased by 38 due to restrictions on human movement. If the government simply activates human movement, there is a possibility that carbon dioxide emissions due to car traffic will increase 39. Therefore, the government needs to combine several policies, such as working from home, online shopping, and active use of public transportation. For example, in order to realize a new lifestyle using public transportation, it is important to design an eas y-t o-walk area. The ease of walking is expected to contribute to the health of the inhabitants 41, the ecological footprint 42, and the future population of 43. The mayor of Paris, Anne Idalgo, advocates the realization of a city for 15 minutes by 2024, and has moved to easy-to-walk areas where people can live without using cars since the COVID-19 Pandemic era. 44. These policies could contribute to the sustainability of cities after COVID-19 pandemic for planners and policy proprieters.
The limit of this study was that only the movement of six types of people published in Google Community Mobility Reports could be analyzed. Therefore, there is no denying that the regulation of the movement of the person proposed by this study may increase the movement of another type and gradually increase the number of infected people. For example, is it really effective to regulate mainly restaurants? In addition, since this study has revealed that urban transportation is not a source of infection, it is necessary to analyze the form of movement, such as public transport, walk, car, etc. In order to deal with this limit, in future research, the movement and movement style of more different types of people should be analyzed using GPS position history data. Such a GPS log data can be obtained regularly from a mobile phone if the user has the consent of the user. For analysis, it is essential to understand the status of users in the GPS position history data. With this data, it is possible to analyze human movement and match infection samples. At present, analyzing such research with big data is difficult from a privacy protection. However, by using such data in the future, the relationship with the number of infections will be more detailed. The limit of this study was that only the movement of six types of people published in Google Community Mobility Reports could be analyzed. Therefore, there is no denying that the regulation of the movement of the person proposed by this study may increase the movement of another type and gradually increase the number of infected people. For example, is it really effective to regulate mainly restaurants? In addition, since this study has revealed that urban transportation is not a source of infection, it is necessary to analyze the form of movement, such as public transport, walk, car, etc. In order to deal with this limit, in future research, the movement and movement style of more different types of people should be analyzed using GPS position history data. Such a GPS log data can be obtained regularly from a mobile phone if the user has the consent of the user. For the analysis, it is essential to understand the infection status of the user of the GPS position history data. With this data, it is possible to analyze human movement and match infection samples. At present, analyzing such research with big data is difficult from a privacy protection. However, by using such data in the future, the relationship with the number of infections will be more detailed. The limit of this study was that only the movement of six types of people published in Google Community Mobility Reports could be analyzed. Therefore, there is no denying that the regulation of the movement of the person proposed by this study may increase the movement of another type and gradually increase the number of infected people. For example, is it really effective to regulate mainly restaurants? In addition, since this study has revealed that urban transportation is not a source of infection, it is necessary to analyze the form of movement, such as public transport, walk, car, etc. In order to deal with this limit, in future research, the movement and movement style of more different types of people should be analyzed using GPS position history data. Such a GPS log data can be obtained regularly from a mobile phone if the user has the consent of the user. For analysis, it is essential to understand the status of users in the GPS position history data. With this data, it is possible to analyze human movement and match infection samples. At present, analyzing such research with big data is difficult from a privacy protection. However, by using such data in the future, the relationship with the number of infections will be more detailed.
In this study, we analyzed people's movements using Google Community Mobility Reports data. This data is open to the public and can see what has changed due to policies aimed at COVID-19 measures. Google Community Mobility Reports has graphed the six categories of retailers / recreation, grocery stores / pharmacies, parks, transportation stations, workplaces, and residential areas. Retail / recreation includes restaurants, cafes, shopping centers, theme parks, museums, libraries, and movie theaters. Food/ pharmacies include grocery stores, food warehouses, farmers markets, specialized food stores, drug stores, and pharmacies. The park includes local parks, national parks, public beaches, marina, dog parks, square, and public gardens. Transportation stations include bases for public transportation such as subway, bus, and railway stations. This data shows a relative change of visitors to six types of locations, compared to the central value of the five weeks from January 3 to February 6, 2020. Google has published changes in visitors in six types of prefectures, not in each location. This study uses data from Osaka, Kyoto and Hyogo prefectures in the Osaka area.
This research protocol has obtained the approval of the Research and Ethics Committee of the Graduate School of Life Sciences at Osaka City University (No. 21-58). In addition, all methods used in this study prohibit the use of GPS data for the purpose of identifying individual users in order to protect the privacy of the GPS location information history of the user. 46 according to the "guidelines on use". Based on the privacy policy, we got informed outlets from all subjects. However, consent is not written because it is digital data. Furthermore, the subject can always stop sending human movement history data by changing the mobile phone settings.
In this study, we analyzed the daily transition of the number of newly determined cases of SARS-COV-2 in three prefectures, Osaka, Kyoto, and Hyogo. The data was obtained from the public information about COVID-19 infection provided by the Ministry of Health, Labor and Welfare in Japan. Published data includes the number of new COVID-19 cases by prefecture. The data does not include information that can identify individuals.
Using the Random Forest Law, we analyzed the relationship between the total number of cases of COVID-19 and the movement data of the human two weeks later. The random forest analysis of this study is an analysis without a teacher. Random Forest predicts the response value by averaging the predicted response values over a large number of decision trees. Each tree grows from the training data boot strap sample. The boot strap specimen is an absolute specimen of the object extracted by replacement. Furthermore, predictive variables are sampled by division of determined trees. Compared to machine learning such as logistic growth models, unnecessary differential equations, neural networks, etc., random forest has a high R 2 score with high accurate models. This is because random forest tends to prevent overtaking. JMP Pro 16. 0 was used for statistical analysis.
Predicated variables are the movement data of people in everyday retail stores / recreation, grocery stores / pharmacies, parks, transportation stations, workplaces, and residential areas. The response variable is the total number of COVID-19 cases two weeks (14 days later). The two-week time lag is because SARS-COV-2 takes about two weeks from infection to onset. In the 10-day prediction of COVID-19 cases, the effectiveness of Google Mobility Data was verified 51. The number of trees in random forest is 10, 000.
The variable scale is all prefectural scale. Regarding the explanatory variables, Google Users were sampled and the population was a prefectural population. This is because 79. 2 % of the population of Japan uses Google.
Based on the results of random forest, this study focused on the R 2 score, main effect, and variable of the predictive profiler. The importance of variables is evaluated by the subordinate re-sample input, which is a factor value built from a combination that has been observed using a recent approach. The evaluated method is useful when the factor may be correlated with each other.
The data shown in this study is available from the 19, 47 literature.
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Acknowledgements

Japanese Language Translation Database System New Influenza Overview of the Law of Special Measures Law. F (Accessed JULY 1 , 2021) (2021).

Research Track ICSME 2024

Osaka Prefecture. Requests for public transportation (subway/bus, etc.), https://www. pref. osaka. lg. jp/attach/40812/004567/kinkyujitaisoch02-0831. pdf SED April 6, 2022) (2021).

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GOMEZ-CRAVIOTO, D. A., DIAZ-RAMOS, R. E., Cantu-ORTIZ, F. J. & Amp; Ceballos, H. G. COVID-19 Disting Data Analysis and Prediction: Comparison of recurrent neural network and time series models. Cognit. Comput.

The use of a deviation-based equation using Google Mobility Data to predict COVID-19 in Arizona. Math. Biosci. Eng 17, 4891-4904 (2020). West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021).

AXSEN, J., Plötz, P. & Amp; Wolinetz, M. Building a strongly integrated policy mix to reduce deep CO2 in road traffic. Nat. Clim. CHANG. 10, 809-818 (2020). Paper Google Scholar

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This study was subsidized by the Japan Academic Promotion Association's Kaken (subsidy number 21k14318) and the Da i-ichi Life Foundation (incentive research). West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021).

15m

The impact of COVID-19 Pandemic in the suburban areas in the metropolitan area of Osaka. Sustain 13, 8974 (2021). Paper CAS Gours Color West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). World Economic Forum. Paris is planning a 1 5-minute city. Available Online, https://www. weforum. org/videos/paris-planning-to-become-A-15-minute-city-city-city-897C12513B (2020). West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021).

10:30-12:00

セッション 2: プログラムの Automatic Repair and Vulnerability 検出 Research トラック＠Furry リーモント 10:30 15m West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021).

10:45

15m West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). 11:00 15m West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021).

11:15

11:30

15m

Study Toropod West Japan Railway Co., Ltd.. News Release: New Railway 13:30-15:00

セッション 3: コード Completion, generation, request Research トラック／Industry トラック（アビノーにて

セッション 2: プログラムの Automatic Repair and Vulnerability 検出 Research トラック＠Furry リーモント

15mStudy Toropod

Research track

Session 4: Software Maintenance and Refactoring Research Track / Journal Fast Track at Fremont

セッション 2: プログラムの Automatic Repair and Vulnerability 検出 Research トラック＠Furry リーモント

13:30

15m

Research Track Dioumidis Spinellis Athens School of Economics and Business & Delft University of Technology, Panos Louridas Athens School of Economics and Business, Maria Kechagia University College London, Tushar Sharma, Dalhousie University West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021).

Research Track

Dorin Pomian, University of Colorado Boulder, Abhiram Bellur, University of Colorado Boulder, Malinda Dilhara, University of Colorado Boulder, Zarina Kurbatova, JetBrains Research, Egor Bogomolov, JetBrains Research, Timofey Bryksin, JetBrains Research, Danny Dig, University of Colorado Boulder, JetBrains Research West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). Research Track Naoki Doi Tokyo Institute of Technology, Yuki Ohsumi Tokyo Institute of Technology, Shinpei Hayashi Tokyo Institute of Technology West Japan Railway Co., Ltd.. News Release: New Railway 13:30 - 15:00

Research Track

14:45 West Japan Railway Co., Ltd.. News Release: New Railway 13:30-15:00 Janderson Santos Federal University of Minas Gerais, Igor Pereira Federal University of Ouro Preto, Eduardo Figueiredo Federal University of Minas Gerais 13:30 - 15:00 West Japan Railway Co., Ltd.. News Release: New Railway 13:30 - 15:00 15:30-17:00 Research Track Dioumidis Spinellis Athens School of Economics and Business & Delft University of Technology, Panos Louridas Athens School of Economics and Business, Maria Kechagia University College London, Tushar Sharma, Dalhousie University West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021).

15:45

James Ivers, Carnegie Mellon University, Anwar Ghammam, University of Oakland, Khouloud Gaaloul, Carnegie Mellon University, Ipek Ozkaya, University of Michigan, Marouane Kessentini, University of Michigan, Flint, Wajdi Aljedaani, University of Michigan Google. Google COVID-19 Community Report Data. 2020). LBMA JAPAN. Guidelines on the use of terminal position information. Https://www. lbmajapan. com/guideline (2020). 15:55 Dorin Pomian, University of Colorado Boulder, Abhiram Bellur, University of Colorado Boulder, Malinda Dilhara, University of Colorado Boulder, Zarina Kurbatova, JetBrains Research, Egor Bogomolov, JetBrains Research, Timofey Bryksin, JetBrains Research, Danny Dig, University of Colorado Boulder, JetBrains Research West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021).

16:10

Naoki Doi Tokyo Institute of Technology, Yuki Ohsumi Tokyo Institute of Technology, Shinpei Hayashi Tokyo Institute of Technology West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021).

16:25

14:45 West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021).

16:40

13:30 - 15:00 Google. Google COVID-19 Community Report Data. 2020). Maha Alhabi KFUPM, Mohamad Al Shave King Fahad Oil Mineral University

15:30-17:00

15:30 15m

Research truck

Federica Pepe, Fiorella Zampetti, University of Sannio (Italy), Antonio Mastropaolo, College of William and Mary (USA), Gabriele Bavouta, Software Institute (Italy), Massimiliano Di Penta, University of Sannio (Italy 15:4510m New ideas, new results Cindy Wouters, University of Brussels-Brie, Koen de Louver, University of Brussels-Brie 15:55 New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). Research track JMP Pro. Prediction Modeling and Special Modeling: Boot Strap Forest: Bootstrap Forest Platform Outline, https://www. jmp. com/support/en/16. 2/

16:1015m

Hastie, T. J., Tibshirani, R. J. & amp; FRIEDMAN, J. THE ELEMENTS OF STATITISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTIRNING: Data mining, inference. 2nd edition (Springer-Verlag, New York, 2009). Google Scholar Nie Pengbo (Shanghai Jiao Tong University), Wang Zihan (Shanghai Jiao Tong University), Wang Chengcheng (East China Normal University), Lin Ziyi (Alibaba Group), He Jiang (Dalian University of Technology), Zhao Jianjun (Kyushu University), Chen Yuting (Shanghai Jiao Tong University 13:30-15:00 15m Research track West Japan Railway Co., Ltd.. News Release: New Railway 13:30-15:00 10m Registration report track West Japan Railway Co., Ltd.. News Release: New Railway 13:30-15:00 Lobby Reception Please join us for a reception in the lobby. West Japan Railway Co., Ltd.. News Release: New Railway 13:30-15:00

Change

09:00 - 10:00 Google. Google COVID-19 Community Report Data. 2020). 15m

Research Track

JMP Pro. Prediction Modeling and Special Modeling: Boot Strap Forest: Bootstrap Forest Platform Outline, https://www. jmp. com/support/en/16. 2/

10:30 - 12:00Session 7: Avinor's Software Architecture and Design Industry Track/Tools and Demo Track

Hastie, T. J., Tibshirani, R. J. & amp; FRIEDMAN, J. THE ELEMENTS OF STATITISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTIRNING: Data mining, inference. 2nd edition (Springer-Verlag, New York, 2009). Google Scholar West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). Industry Track This study was subsidized by the Japan Academic Promotion Association's Kaken (subsidy number 21k14318) and the Da i-ichi Life Foundation (incentive research). West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021).

Industry Track

The impact of COVID-19 Pandemic in the suburban areas in the metropolitan area of Osaka. Sustain 13, 8974 (2021). Paper CAS Gours Color Google. Google COVID-19 Community Report Data. 2020). LBMA JAPAN. Guidelines on the use of terminal position information. Https://www. lbmajapan. com/guideline (2020).

Tool Demo

09:00 - 10:00 West Japan Railway Co., Ltd.. News Release: New Railway 13:30-15:00

Chair: AJAY JHA North Dakota State University

セッション 2: プログラムの Automatic Repair and Vulnerability 検出 Research トラック＠Furry リーモント 15m West Japan Railway Co., Ltd.. News Release: New Railway 13:30-15:00

10:45

15m Google. Google COVID-19 Community Report Data. 2020). LBMA JAPAN. Guidelines on the use of terminal position information. Https://www. lbmajapan. com/guideline (2020).

11:00

15m West Japan Railway Co., Ltd.. News Release: New Railway 13:30-15:00

11:15

15m Google. Google COVID-19 Community Report Data. 2020). LBMA JAPAN. Guidelines on the use of terminal position information. Https://www. lbmajapan. com/guideline (2020).

11:30

10m West Japan Railway Co., Ltd.. News Release: New Railway 13:30-15:00 11:40 15m West Japan Railway Co., Ltd.. News Release: New Railway 13:30 - 15:00

13:30-15:00

13:30 Google. Google COVID-19 Community Report Data. 2020). Maha Alhabi KFUPM, Mohamad Al Shave King Fahad Oil Mineral University

DAKSH CHAUDHARY Ottawa University, Sri Lakshmi Vadlamani Ericsson, Dimple Thomas Ericsson, SHIVA NEJATI University, Mehrdad Sabetzadeh University

セッション 2: プログラムの Automatic Repair and Vulnerability 検出 Research トラック＠Furry リーモント 10m Research Track Dioumidis Spinellis Athens School of Economics and Business & Delft University of Technology, Panos Louridas Athens School of Economics and Business, Maria Kechagia University College London, Tushar Sharma, Dalhousie University West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021).

Industrial truck

New ideas and new results trucks

Ain M. T. Buy Hanoi Science and Technology University, Guen Du k-Rock Hanoi Science and Technology University West Japan Railway Co., Ltd.. News Release: New Railway 13:30-15:00

Industry truck

Doug Dalum Don'T Panic Labs, Bonita Shalif US Nebraska University Lincoln West Japan Railway Co., Ltd.. News Release: New Railway 13:30-15:00

Journal First Truck

Gregorio Robreslay Van Carlos University, Michel Shedron Einthin Institute of Technology (Netherlands), Roddy Jolax RISE Research Institute (Sweden), Midsweden University, Regina Hevich University (Germany Rostock University Google. Google COVID-19 Community Report Data. 2020). LBMA JAPAN. Guidelines on the use of terminal position information. Https://www. lbmajapan. com/guideline (2020).

Registration Report Truck

13:30 - 15:00 West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021).

15:30-17:00

15:45

16:00

16:15

15m Google. Google COVID-19 Community Report Data. 2020). Maha Alhabi KFUPM, Mohamad Al Shave King Fahad Oil Mineral University

16:30

Doug Dalum Don'T Panic Labs, Bonita Shalif US Nebraska University Lincoln West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021).

16:40

15:30-17:00

13:30 - 15:00 Google. Google COVID-19 Community Report Data. 2020). LBMA JAPAN. Guidelines on the use of terminal position information. Https://www. lbmajapan. com/guideline (2020).

Marcel HOMOLKA Linka Johannesque Pla University Software System Institute of Engineering, Luciano Marchezan Linz Johannesque Pla University, Wesley AssunsunçãO North Carolina State University, Alexander Egyed Linz Johanneskle University

15:45 Google. Google COVID-19 Community Report Data. 2020). LBMA JAPAN. Guidelines on the use of terminal position information. Https://www. lbmajapan. com/guideline (2020). Md Rayhanul Masud University of California, Riverside, Md Omar Faruk Rokon Sponsored Search, Walmart Global Tech, Qian Zhang University of California, Riverside, Michalis Faloutsos UCR 15:55 15:4510m Ozren Dabik Italian University Software Institute (Switzerland), Rosaria Tufano Italian University Software Institute (Italy), Gabriele Bavota Italian University Software Institute (Italy 16:05 10m New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). Rey Juan Carlos University, Rey Juan Carlos University, Rey Juan Carlos University, Rey Juan Carlos University, Rey Juan Carlos University 16:15 New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). Research Track JMP Pro. Prediction Modeling and Special Modeling: Boot Strap Forest: Bootstrap Forest Platform Outline, https://www. jmp. com/support/en/16. 2/

16:3010m

Hastie, T. J., Tibshirani, R. J. & amp; FRIEDMAN, J. THE ELEMENTS OF STATITISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTIRNING: Data mining, inference. 2nd edition (Springer-Verlag, New York, 2009). Google Scholar West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). 10m This study was subsidized by the Japan Academic Promotion Association's Kaken (subsidy number 21k14318) and the Da i-ichi Life Foundation (incentive research). Google. Google COVID-19 Community Report Data. 2020). Maha Alhabi KFUPM, Mohamad Al Shave King Fahad Oil Mineral University

10m

Research track West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021).

Display time Mountain Time (USA/Canada)

Registration report track West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). 35m Please join us for a reception in the lobby. Google. Google COVID-19 Community Report Data. 2020). Maha Alhabi KFUPM, Mohamad Al Shave King Fahad Oil Mineral University

Research Track

Aniket Potdar, Emad Shihab Concordia University Google. Google COVID-19 Community Report Data. 2020). 15m

Chair: Tushar Sharma Dalhousie University

World Economic Forum. Paris is planning a 1 5-minute city. Available Online, https://www. weforum. org/videos/paris-planning-to-become-A-15-minute-city-city-city-897C12513B (2020). West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021).

Yuangan Zou, Xinpeng Shan, Shiqi Tan, Shurui Zhou University of Toronto

JMP Pro. Prediction Modeling and Special Modeling: Boot Strap Forest: Bootstrap Forest Platform Outline, https://www. jmp. com/support/en/16. 2/

10mRegistration Report Track

Hastie, T. J., Tibshirani, R. J. & amp; FRIEDMAN, J. THE ELEMENTS OF STATITISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTISTIRNING: Data mining, inference. 2nd edition (Springer-Verlag, New York, 2009). Google Scholar West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). Research Track This study was subsidized by the Japan Academic Promotion Association's Kaken (subsidy number 21k14318) and the Da i-ichi Life Foundation (incentive research). West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021).

Research Track

Registration and Report Track

Tool demo

Research truck

World Economic Forum. Paris is planning a 1 5-minute city. Available Online, https://www. weforum. org/videos/paris-planning-to-become-A-15-minute-city-city-city-897C12513B (2020). West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021).

Chair: Ronnie de Souza Santos Calgary University

セッション 2: プログラムの Automatic Repair and Vulnerability 検出 Research トラック＠Furry リーモント 15m West Japan Railway Co., Ltd.. News Release: New Railway 13:30 - 15:00

10:45

11:00

11:15

11:30

15m Google. Google COVID-19 Community Report Data. 2020). 15m 11:45 15m Google. Google COVID-19 Community Report Data. 2020). 15m

11:15

13:30 Google. Google COVID-19 Community Report Data. 2020). LBMA JAPAN. Guidelines on the use of terminal position information. Https://www. lbmajapan. com/guideline (2020).

Lu Xiao Stevens Institute of Technology, Gengwu Zhao Stevens Institute of Technology, Xiao Wang Stevens Institute of Technology, Qi Li Stevens Institute of Technology, Eric Lim Stevens Institute of Technology, Chenhao Wei Stevens Institute of Technology, Tingting Yu University of Connecticut, Xiaoying Wang University of Texas at San Antonio

セッション 2: プログラムの Automatic Repair and Vulnerability 検出 Research トラック＠Furry リーモント 15m Nie Pengbo (Shanghai Jiao Tong University), Wang Zihan (Shanghai Jiao Tong University), Wang Chengcheng (East China Normal University), Lin Ziyi (Alibaba Group), He Jiang (Dalian University of Technology), Zhao Jianjun (Kyushu University), Chen Yuting (Shanghai Jiao Tong University 13:30-15:00 14:00 15m West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). 14:15 15m West Japan Railway Co., Ltd.. News Release: New Railway 13:30-15:00 14:30 10m West Japan Railway Co., Ltd.. News Release: New Railway 13:30 - 15:00

14:40

15m Google. Google COVID-19 Community Report Data. 2020). LBMA JAPAN. Guidelines on the use of terminal position information. Https://www. lbmajapan. com/guideline (2020).

14:50

Research Track

New Ideas and New Results Track

Dioumidis Spinellis Athens School of Economics and Business & Delft University of Technology, Panos Louridas Athens School of Economics and Business, Maria Kechagia University College London, Tushar Sharma, Dalhousie University West Japan Railway Co., Ltd.. News Release: New Railway New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021).

25m

15m

Ain M. T. Buy Hanoi Science and Technology University, Guen Du k-Rock Hanoi Science and Technology University Google. Google COVID-19 Community Report Data. 2020). 15m

11:30

Naoki Doi Tokyo Institute of Technology, Yuki Ohsumi Tokyo Institute of Technology, Shinpei Hayashi Tokyo Institute of Technology Google. Google COVID-19 Community Report Data. 2020). 15m

15m

Journal Fast Track Google. Google COVID-19 Community Report Data. 2020). 15m

Gregorio Robreslay Van Carlos University, Michel Shedron Einthin Institute of Technology (Netherlands), Roddy Jolax RISE Research Institute (Sweden), Midsweden University, Regina Hevich University (Germany Rostock University West Japan Railway Co., Ltd.. News Release: New Railway 13:30-15:00

Session 16: Software Development Process and Tools Demo Track / Industry Track / Research Track at Fremont

15:30 Google. Google COVID-19 Community Report Data. 2020). 15m

Registration and Report Track

15:45

15m

Not scheduled yet

New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021).

Information for Participants

Tajmilur Rahman University of Saskatchewan, Yuecai Zhu Bell Mobility, Lamyea Maha University of Saskatchewan, Chanchal K. Roy University of Saskatchewan, Canada, Banani Roy University of Saskatchewan, Kevin Schneider University of Saskatchewan

15m

Accepted Papers

New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021). New common sense and safety of the railway, https://www. westJr. co. jp/press/article/items/210218_00_newway. pdf (Accessed April 6, 2022) (2021).

Call for Papers

Goal and Scope

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The 40th IEEE IEEE International Conference on Software Maintainance (ICSME 2024) has announced the latest technological innovation, trends, experiences, and issues on software maintenance and evolution This is the forum. We are looking for hig h-quality papers related to the following software maintenance and evolutionary topics (alphabetical order), which explain important and unpublished results:
Change and defective management
Code cloning and source

Concept and arrangement of functions

Continuous integration / deployment

Evaluation

Demonstration research on software maintenance and evolution

Author Response Period

Evolution of products other than cords

NEW IN 2024: Early Decisions

Evolution and maintenance of A I-based applications

Human aspects of software maintenance and evolution

Publication and Presentation

Large language model for software evolution and maintenance work

Paper Submission

Mode l-based method maintenance and evolution

Mobile app maintenance and evolution
Servic e-oriented and cloud computing systems maintenance and evolution
Process of maintenance and evolution
Comparison of maintenance and release

Software positive mining

Productivity of software engineers in maintenance and evolution

Submission

Release engineering

Open Science Policy

Reverse engineering and revenge

Ranime Evolution and Dynamic Configuration

Understanding software and system

Migration and renovation of software

Software quality evaluation

Important Dates

Software refactoring and reconstruction

Software test theory and practice
Source code analysis and operation
Technical debt
ICSME welcomes innovative ideas that are timely, well presented and evaluated. All posts must be positioned in the existing documents, explaining that the results are related to the specific software engineering goals, and include clear motives and presentations. All posts should be done in English and follow the following paper posting.
All papers must be full paper.

Track Co-Chairs

Those who do not comply with the prescribed submitted form, or deviated from the scope of the tournament will be rejected on the desk without being judged. All posts that meet the submission standards and match the scope of the tournament will be judged by three program members. All posts are evaluated for the importance of contribution, the creativity, the quality of the presentation, the quality of the presentation, the evaluation (if applicable), and the appropriate comparison with related research. In case of applicable (eg, evaluation empirical research and other technical contributions), the reproducibility of the research is also evaluated.

ICSME 2024 provides a 7-day author response period. During this period, the author is given the opportunity to view the reviews and answer certain questions raised by the Program Committee. This period is set up after all the examination is completed, the deliberation is made, and it is reflected in the subsequent decision process. As part of the author's answer process, the author can browse the full review of the reviewers, including the scoring of the reviewer. Human aspects of software maintenance and evolution

Elim Poon - Journalist, Creative Writer

Last modified: 27.08.2024

It is essential to control the human mobility of groceries/pharmacies to between −5 and 5% and that of parks to more than −20% and the most significant. green areas, and the like (excluding large water and forest areas). After Human mobility and infection from Covid in the Osaka metropolitan area. Human mobility and infection from Covid in the Osaka metropolitan area. npj Urban Sustainability. | Journal article. DOI: /s

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accepted

Human mobility and infection from Covid19 in the Osaka metropolitan area npj Urban Sustainability

Human mobility and infection from Covid-19 in the Osaka metropolitan area

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Non-compulsory measures sufficiently reduced human mobility in Tokyo during the COVID-19 epidemic

Assessment of the impact of reopening strategies on the spatial transmission risk of COVID-19 based on a data-driven transmission model

Impact of urbanisation and environmental factors on spatial distribution of COVID-19 cases during the early phase of epidemic in Singapore

Introduction

Results

Changes in human mobility

Change in the Number of COVID-19 Cases

Human mobility types that impact the number of COVID-19 cases

Discussion

Methods

Human mobility data

Number of COVID-19 cases data

Statistical analysis

Data availability

References

Acknowledgements

Research Track ICSME 2024

Not scheduled yet

Information for Participants

Accepted Papers

Call for Papers

Goal and Scope

Evaluation

Author Response Period

NEW IN 2024: Early Decisions

Publication and Presentation

Paper Submission

Submission

Open Science Policy

Important Dates

Track Co-Chairs