City Map Research Articles

A Multi-Modal Approach for A Healthier Weight and More Active Lifestyle

Abstract Background Obesity and overweight has been increasing globally and in the UK over the last few years, bringing along a wide array of challenges in health and wellbeing. Not only do they take a heavy toll on those affected, but obesity and overweight-related ill-health is costing the UK National Health Service £6.1 with projected costs to run up to £9.7 billion in 2050. This project aimed to apply artificial intelligence to identify the predictive indicators for obesity and co-create an intervention with public health practitioners and stakeholders. Methods Using health and wellbeing public health population data from the 2015, 2018 and 2022 from a city in the East Midlands, we applied artificial intelligence that uses machine learning techniques to discover insights, find hidden patterns and discover relationships in the data about engaging in physical activity and a healthy diet. The data on dietary choices and physical activity preferences were further analysed using advanced machine learning techniques. Results The outcomes from our machine learning process revealed patterns of physical activity engagement and diet from specific locations, along with a range of demographic variables that influence individuals’ patterns of physical ability and dietary practices. These findings, which will be presented in detail, have been integrated into a comprehensive city map. This map not only showcases opportunities for engaging in a healthy lifestyle but also aids in prioritising interventions in areas of greatest need. Conclusions The AI technology we employed allowed us to parameterise and generalise our findings with the possibility of scaling up the machine learning approach to other similar datasets. The findings facilitated the development of bespoke training for public health officers working with underserved communities, further demonstrating the impact of applying AI to inform the design of public health interventions. Key messages • Applying Artificial Intelligence to public health data has the potential to inform the development of effective interventions and increase precision. • Using AI in public health data can generate new insights into population health and well-being and inform public health policy.

Assessment of the risk to the health of the population living in the zone influenced by atmospheric emissions from the engineering industry

Introduction. During operation, machine-building enterprises emit pollutants that can negatively affect the health of the population. The study aims to determine the impact of emissions from a machine–building plant, as well as background atmospheric pollution, on the health risk of the population of Novokuznetsk. Materials and methods. The work used data from the volume of maximum permissible emissions of a machine-building plant. The researchers calculated the maximum and average concentrations of pollutants using the "ECOcenter – Standard" program at 36 exposure points selected on the city map. Experts determined the maximum permissible concentrations of pollutants in the atmosphere in accordance with SanPiN 1.2.3685-21. The authors calculated the risks to public health in accordance with the Guidelines R 2.1.10.1920-04. The classification of risk levels was carried out on the basis of MP 2.1.10.0156-19. 2.1.10. Scientists also made a risk assessment considering background atmospheric pollution. Results. Specialists carried out a risk assessment from exposure to nitrogen dioxide, carbon monoxide, sulfur dioxide, carbon (soot), inorganic dust, hexavalent chromium. The maximum and average concentrations of pollutants, as well as the maximum concentrations calculated taking into account background pollution, did not exceed the maximum permissible level. The average concentrations of nitrogen dioxide and hexavalent chromium, taking into account the background, exceeded the hygienic standard. The values of the hazard indices for acute and chronic exposures without taking into account the background, as well as for acute exposures taking into account the background, corresponded to the minimum (target) risk level. The values of the hazard indices for chronic inhalation effects, considering the background, corresponded to the alarming risk level at five points, amounting to 3.084–3.800. With chronic exposure, taking into account the background, an alarming level of risk was revealed for the effect on the respiratory organs (at four points the hazard index was 3.117 to 3.616) and blood (at three points the hazard index was in the range from 3.090 to 3.433). The total individual carcinogenic risk, excluding background, did not exceed the permissible level, ranging from 1.08×10–8 to 2.43×10–7 at different points, taking into account the background, amounted to 1.79×10–4–2.26×10–4, which corresponds to an alarming level. Hexavalent chromium makes the main contribution to the formation of carcinogenic risk. Limitations. Calculated concentrations of pollutants were used to assess the risks. Conclusion. The risks from exposure to atmospheric emissions from the machine-building plant correspond to the minimum (target) level. Background concentrations of toxic substances in chronic inhalation exposures determine an alarming level of non-carcinogenic risk at five points, as well as an alarming level of carcinogenic risk at all points of exposure. Ethics. This study did not require the conclusion of the Ethics Committee.

Reinforcement Learning-Based Adaptive Optimal Control Model for Signal Light in Intelligent Transportation Systems

Day-to-day mobility among the population has increased with economic growth. Smart cities are renovated with advanced technologies to admire modern life in which intelligent transportation becomes highly focused. Because the traffic signal control systems are fixed at a constant time. They split the traffic signal into predetermined intervals and function inefficiently; they result in long wait times, waste fuel and increased carbon emissions. This research study introduces a novel technique for traffic light management to reduce the uncertainties in the system. A dynamic and intelligent traffic light adaptive optimal management system (DITLAOCS) is implemented in this research. It does this by modifying the traffic signal duration in run time and using real-time traffic data as input. Furthermore, the proposed DITLAOCS executes based on three modes: fairness mode (FM), priority mode (PM) and emergent mode (EM). In fairness mode (FM), all vehicles are prioritized equally, while vehicles in different categories receive varying priority levels. Emergency vehicles, on the other hand, receive the highest priority. Furthermore, a fuzzy inference method based on traffic data is shown to choose one mode out of three (FM, PM and EM). This model uses deep reinforcement learning to switch traffic lights in three different phases (red, green and yellow). We evaluated and accurately simulated DITLAOCS on the Shaanxi city map in China using Simulation of Urban MObility (SUMO), an open-source simulator. The simulation results illustrate the efficiency of DITLAOCS when compared to other cutting-edge algorithms on several performance measures.

Chip-scale atomic clock (CSAC) aided GNSS in urban canyons

In urban canyons, the reflections and obstructions of Global Navigation Satellite System (GNSS) signals frequently lead to significant errors in measurements, the number of which can be larger than that of the correct measurements. This leads to a severe degradation of GNSS performance in urban canyons. Various fault detection and exclusion (FDE) algorithms have been developed to cope with these outliers caused by multipath effects. Most of these FDE algorithms check the consistency among measurements. However, in urban canyons, their effectiveness is significantly compromised by the lack of fault-free measurements. There is an urgent need to develop new constraints for enhancing GNSS FDE performance. In recent years, the advent of Chip-Scale Atomic Clock (CSAC), known for their affordability and high frequency stability, offers a promising solution for accurately predicting receiver clock errors. Additionally, using city maps to establish height constraints is another way to increase redundancy. The purpose of this study is to improve the GNSS positioning accuracy in urban canyons with the aid of CSAC and city map data. A novel FDE algorithm is developed to search for positions through the constraints of height and receiver clock. Extensive tests were conducted in urban canyons to evaluate the performance of the system. Results showed that the positioning accuracy can be improved from tens of meters to less than 6 m.

Language learning space and legitimation of adult second language speakers in the workplace

ABSTRACT This paper explores space in relation to the (il)legitimacy of migrants as second language learners and speakers. Migrants learn the host country’s language(s) in multiple settings, both in language classrooms and beyond in various institutional and non-institutional settings. The workplace is a crucial setting for many migrant language learners. Applying the concept of positioning (Bamberg [1997]. Positioning between structure and performance. Journal of Narrative and Life History, 7(1–4), 335–342. https://doi.org/10.1075/jnlh.7.42pos; Bamberg & Georgakopoulou [2008]. Small stories as a new perspective in narrative and identity analysis. Text & Talk, 28(3), 377–396. https://doi.org/10.1515/TEXT.2008.018) to focus group discussions with four female highly educated migrants from Indonesia who recently came to Norway, the present paper explores the meanings and roles of space and place in the legitimacy of Norwegian language learners. As part of the focus group discussions, a city map was used to elicit the participants’ narratives. The findings illustrate that legitimacy as language learners and speakers is constantly negotiated and renegotiated in various learning spaces. Different spaces may be associated with different language ideologies shaping the power structures that affect how learners can be perceived as legitimate or illegitimate speakers. This study contributes new insights into the role of spaces in language learning and legitimisation of second language speakers, in particular, adult learners in a non-English-speaking country.

Understanding the spatial pattern and structural characteristics of cities in late feudal China: evidence from the local chronicle maps of the qing dynasty (1644–1911)

ABSTRACT Our study analyzes the spatial pattern and structural characteristics of cities in late feudal China based on multiple correlation and geographic information system spatial analysis, using 58 local Chinese chronicle maps of Jiangsu in the Qing Dynasty as research material. The elements in the city map were dominated by the types of official buildings, transportation facilities, and religious buildings. The urban spatial pattern can be classified into four types, such as extraverted and introverted, with each type having an aggregated spatial distribution and a gradual introverted orientation in time. The urban spatial structure can also be divided into four types: traditional, axial, random, and composite. Spatial distribution of each type is relatively stable, with little change over time. The geographic environment and the traditional concept of city building are the basic reasons for the formation of the spatial pattern and structure. The flood disaster, commercial and military factors contribute to the diverse structures. Our study demonstrates the feasibility of quantifying the ancient Chinese chronicles’ city maps. The findings have important value for contemporary ancient city restoration and shaping urban characteristics.

Crowdsourced Geospatial Intelligence: Constructing 3D Urban Maps with Satellitic Radiance Fields

In urban planning and research, 3D city maps are crucial for activities such as cellular network design, urban development, and climate research. Traditionally, creating these models has involved costly techniques like manual 3D mapping, interpretation of satellite or aerial images, or the use of sophisticated depth-sensing equipment. In this work, we propose a novel approach to develop 3D urban maps by examining the influence of urban structures on satellite signals, using GPS records crowdsourced from hundreds of smartphones during everyday user movements. We introduce the concept of satellitic radiance fields (SaRF), a novel neural scene representation technique designed to capture the distribution of GPS signals in urban settings. SaRF employs a sparse voxel octree framework to depict voxel-centric implicit fields, capturing physical properties like the density of each voxel. This model is progressively refined using a differentiable ray-marching process, ultimately leading to the reconstruction of 3D urban maps. Our thorough experimental evaluation, which incorporates approximately 27.4 million GPS records, reveals an average reconstruction accuracy of 83.1% in six varied urban scenes.

Exploring the effects of urban network topologies on entropy trajectories of segregation

Segregation is a threat to the aspirations of producing a cohesive society and modelling its dynamics can be done in order to help design preventative measures. This work explores the question of whether the network topologies of urban spaces can affect the pace at which populations can become segregated. The simulation dynamics employed augment the canonical Schelling model in such a way that it also captures the affinity for agents to prefer denser regions which also offer sufficient local homogeneity. It is shown that different networks synthetically generated and from real city maps can alter the rate of segregation. The results also show that using the entropy trace on the distribution of agent edge degree across all agents correlates with the segregation reinforcing the relevance of physics inspired modeling of social systems. This investigation shows that it is possible to explore and select network arrangements which can be less conducive towards segregation movements during the stages of urban planning so that the rate is reduced. An additional finding is that the entropic measure is closely associated with the common statistic for such modeling efforts.

City-Scale Air Quality Network of Low-Cost Sensors

In this paper, we present a city-scale (possibly global) air pollution network made of low-cost sensors for particulate matter concentration in the air. The components of the presented system are based on our research and experience from previous studies focused on air quality instruments and sensors for addressing urban air pollution. Sensor nodes are produced locally and distributed over Sarajevo, Bosnia and Herzegovina. The system collects, calibrates, and displays particulate matter concentrations in real-time. In comparison to the available measurements from governmental institutions, our system demonstrated good agreement of measured parameters, with several advantages including, higher resolution in space and time, lower costs, both horizontal and vertical measurements. One of the capabilities of the system is the real-time air pollution city map with animations. By installing multiple sensor nodes over a slope, we receive vertical measurements of temperature, humidity, and particulate matter concentration in real time, which gives a valuable insight into the dynamics of temperature inversion episodes and air pollution below the inversion layer.

Using fuzzy analytical hierarchy process for road transportation services management based on remote sensing and GIS technology

Abstract The importance of site selection for road transportation management and emergency services has been underscored, particularly in the wake of the global Covid-19 pandemic in addition to road accident injuries, which emphasized the need for swift patient, injured and wounded peoples transfer to hospitals. As a result, comprehensive road transportation management is essential during crises to ensure the safety and convenience of road users. To achieve effective road network management, a robust database is imperative. The aim of this study is to employ multi-criteria decision analysis with the aid of Geographical Information System (GIS) technology and remote sensing for the optimization of site selection for traffic signals, fire stations, and emergency services in Kafr El-Sheikh city, Egypt. The methodology incorporates two different methods which are Fuzzy Analytical Hierarchy Process (F-AHP) and the spline transformation method. The integration of Fuzzy set theory with AHP principles has given rise to a variant of AHP known as F-AHP. F-AHP combines qualitative and quantitative approaches. Fuzzy logic handles situations that are vague or poorly defined by assigning numerical values. Through the F-AHP approach, criteria that decision-makers unanimously deem “absolutely not important” in comparison to others are eliminated, allowing them to focus on the most significant criteria. As a case study, an Egyptian city was selected to apply these techniques. The results revealed multiple sites that were identified and selected through the applied analytical methods. These selected sites were also marked on the city map and verified in reality.

An exploration of urban air health navigation system based on dynamic exposure risk forecast of ambient PM2.5

Under international advocacy for a low-carbon and healthy lifestyle, ambient PM2.5 pollution poses a dilemma for urban residents who wish to engage in outdoor exercise and adopt active low-carbon commuting. In this study, an Urban Air Health Navigation System (UAHNS) was designed and proposed to assist users by recommending routes with the least PM2.5 exposure and dynamically issuing early risk warnings based on topologized digital maps, an application programming interface (API), an eXtreme Gradient Boosting (XGBoost) model, and two-step spatial interpolation. A test of the UAHNS’s functions and applications was carried out in Wuhan city. The results showed that, compared with trained random forest (RF), LightGBM, Adaboost models, etc., the XGBoost model performed better, with an R2 exceeding 0.90 and an RMSE of approximately 15.74 μg/m3, based on data from national air and meteorological monitoring stations. Further, the two-step spatial interpolation model was adopted to dynamically generate pollution distribution at a spatial resolution of 300 m*300 m. Then, an exposure comparison was performed under randomly selected commuting routes and times in Wuhan, showing the recommended routes for lower PM2.5 exposure made effectively help. And the route difference ratios of about 14.9 % and 16.9 % for riding and walking, respectively. Finally, the UAHNS platform was integrally realized for Wuhan, consisting of a real-time PM2.5 query, a one-hour PM2.5 prediction function at any location, health navigation on city map, and a personalized health information query.

‘Such a Space to Cross’: Lessons Learned(?) from Teaching During a Pandemic

ABSTRACT The COVID-19 Pandemic dramatically impacted the classroom experiences of teachers and students across the globe. This reflexive autobiographical article critically examines the ramifications of this extraordinary event on the experiences of teaching and learning for the teacher-writer and her secondary English and literature students. Through a process of narrative inquiry , the text weaves together stories of praxis during and after the extended lockdowns experienced in Victoria, Australia, with exploration of spatial and geographical metaphors through which the teacher seeks to derive meaning from her experiences of teaching while physically distanced from her students and colleagues. These reflections are theorised using Doreen Massey’s conceptualisation of space as both social and political and Michel de Certeau’s metaphor of the city map in order to illuminate the impacts of the altered learning landscape on the teacher’s professional identity during and after the COVID-19 Pandemic. In this way, the essay also offers a critical reflection on the consequences of reification in school communities that are inevitably shaped by standards-based reforms and institutional power.

Knowledge-Based Identification of Urban Green Spaces: Allotments

Abstract. Urban Green Spaces (UGS) play a crucial role in enhancing the quality of life in cities by providing numerous environmental, social, and health benefits. Among these green spaces, allotment gardens stand out as a unique type that contributes to ecological services, preservation of biodiversity, and the overall well-being of urban dwellers. Unfortunately, the significance of allotment gardens as a specific type of UGS is still disregarded and they are not recognized as a separate category in land use / land cover maps or city maps of green spaces. This is mainly due to the mixed use of allotment areas, their small size and absence of tailored identification or mapping workflows. In this research, we address the latter one by proposing an approach that utilizes various semantic characteristics of allotment gardens to create distinctive spatial representations. The semantic characteristics we consider include the presence, density, and height of garden huts, proximity to water bodies and railroads, as well as the presence of pathways within the allotment gardens. Allotments are delineated using a three-step procedure. This involves utilizing a Random Forest machine learning classifier to create maps of the distribution of green spaces, extracting garden huts employing a threshold, and demarcating the area using a density based clustering technique. Furthermore, we repeat the same workflow in a new study area to assess the applicability of the proposed workflow. With the established workflow, we are able to accurately identify 78% of allotments in Augsburg and 88% in Wuerzburg respectively. Our results demonstrate that the proposed workflow can be a useful approach to validate and extend existing land use and land cover data sets while remaining time and cost effective.

Mathematical Connections of Students Viewed From Adversity Quotient in Problem-Based Learning Using Math City Map

Mathematical Connections of Students Viewed From Adversity Quotient in Problem-Based Learning Using Math City Map

Divergent and Convergent Creativity Are Different Kinds of Foraging

According to accounts of neural reuse and embodied cognition, higher-level cognitive abilities recycle evolutionarily ancient mechanisms for perception and action. Here, building on these accounts, we investigate whether creativity builds on our capacity to forage in space (“creativity as strategic foraging”). We report systematic connections between specific forms of creative thinking—divergent and convergent—and corresponding strategies for searching in space. U.S. American adults completed two tasks designed to measure creativity. Before each creativity trial, participants completed an unrelated search of a city map. Between subjects, we manipulated the search pattern, with some participants seeking multiple, dispersed spatial locations and others repeatedly converging on the same location. Participants who searched divergently in space were better at divergent thinking but worse at convergent thinking; this pattern reversed for participants who had converged repeatedly on a single location. These results demonstrate a targeted link between foraging and creativity, thus advancing our understanding of the origins and mechanisms of high-level cognition.

The association of the physical and social environment with mortality in urban areas: an ecological study on the city of Bologna, Italy.

The urban environment influences health through many pathways. The aim of the present study was to map the distribution of mortality, environmental predictors (distribution of green areas and transport networks), and social predictors (income deprivation) in the mid-sized city of Bologna (Italy), and to analyse the relationship between these variables. The study employed an ecological cross-sectional design using data from public sources. The units of analysis were the 18 city districts. The percentage of green areas, percentage of transport networks and age-standardised mortality rates were calculated for each district. These variables, and an indicator of income deprivation, were plotted on the city map to analyse their distribution. Simple and multiple linear regressions with mortality as the outcome and environmental and social data as predictors were run. The results showed an unequal distribution of the variables in the city, with the north-eastern districts presenting worse values. Green areas did not result significantly in being related to mortality. The income indicator and transport networks have an impact on mortality in the simple regression, but only transport networks were found to have a statistically significant relation with mortality in the multiple regression. The results suggested that living close to major transport networks could affect mortality rates in the city, but further research is needed. Future studies are also needed to analyse the interaction between environmental exposures and socioeconomic factors in affecting health. These findings can be useful for urban planning and health promotion interventions.

Comprehension of City Map Pictograms Designed for Specific Tourists’ Needs

Comprehension of City Map Pictograms Designed for Specific Tourists’ Needs

Повернення з небуття: Скидан Микола Антонович (1894-1954 рр.).

In the mid-1990s, on the initiative of Oksana Pelenska – at that time a researcher of Ukrainian emigration in the interwar Czechoslovak Republic and head of the office of the Embassy of Ukraine in the Czech Republic, and now an employee of the "Ukrainian Editorial Board of Radio Svoboda" – the project "Ukrainian addresses in Prague" was launched (still active). Thus, on the map of Prague, Poděbrady , Brno, and other Czech cities, Ukrainian addresses are gradually "discovered," such as Luzhytska Street 38, apartment 1 (the place of registration of the publisher Petr Zlenka); 6 Goremyrova Street (the main estate of the Museum of the Liberation Struggle of Ukraine). Therefore, the purpose of the study is to supplement information about "Ukrainian addresses in Prague" through the prism of the biography of Mykola Antonovych Skydan. The research methodology is based on the principles of concrete-historical approach or historicism, objectivity, comprehensiveness, integrity, systematicity, as well as the use of methods of analysis, synthesis, historical-genetic, historical-comparative, historical-typological, problem-chronological. The scientific novelty lies in the publication of previously unknown information about the life and activities of the agronomist and publisher, permanent secretary of the Foreign Committee of the Ukrainian Party of Socialist Revolutionaries in the Czechoslovak Republic Mykola Antonovych Skydan. Conclusions. Mykola Antonovych Skydan entered the field of view of the "liberators of Prague" by accident in May-June 1945. He, like statesman Mykola Rossinevych, professor of classical languages Mykola Tymchenko, and publisher Petro Zlenko, was captured, interrogated, sent, and transported to Lukyanivska prison and later accused of anti-Soviet activities. The sentence was 10 years of correctional labor. Skydan did not live to the end of his prison term. The author of this publication is so far the only person who has inquired about the rehabilitation certificate of Mykola Antonovych Skydan.

Between Parametricism and Pragmatism Concept Design Problematics in Zaha Hadid Architects’ Digital Projects

This study provides a comprehensive analysis of the challenges in Zaha Hadid Architects' parametrical projects, focusing on recent digital technologies in the realms of "Architecture" and "Urban planning." Recently, Zaha Hadid Architects “urban-scale" project has awarded the title of "Parametric-urbanism" introduced a new urban design term to the world. This research delves into the design and implementation issues encountered in the Istanbul Kartal-Pendik Master Plan, parametric design which planned non-realistic, and fluiding plots and parcels not dependent on the city maps. 20<sup>th</sup> century early urban planning doctrines of C. Sitte and some French urbanists known as pragmatists, and realistic. The study expected to contribute design discourse with new approach parametric projects via French pragmatists problem solving methods. A comparative method is used to analyze the late 20th century parametric theories, and urbanism ideologies of 20th century; CIAM, Le Corbusier and French urbanists’ “realistic” and “problem-solving” methods. Zaha Hadid Architects’ “urban-scale” projects created via abstractions of parametric repetitive forms considered problematic. Some inconsistencies are observed in design and implementation process secondary parametric urban elements; road, axis, plot, parcel, block design and dimensions. Also, the urban scale parametric projects can be problematic in complicated, old, historical cities like Rome, Paris, Istanbul.

SUBSYSTEM FOR MONITORING ATMOSPHERIC AIR QUALITY IN THE CYBER-PHYSICAL SYSTEM "SMART CITY"

The task of designing and developing a cyber-physical system "Smart City" is currently relevant for Ukraine. This study is devoted to the development of a method and subsystem for monitoring atmospheric air quality in the cyber-physical system "Smart City". The article develops a method for monitoring atmospheric air quality, which forms the basis for effective monitoring of atmospheric air quality in the cyber-physical system "Smart City" and allows making informed decisions on warning residents about the danger with recommendations for protecting their health. The developed subsystem for monitoring atmospheric air quality in the cyber-physical system “Smart City” collects data from the installed sensors of air humidity, air temperature, dust content in the air, air radiation background, air pollution level by nitrogen oxides, air pollution level by sulfur, air pollution level by carbon compounds, air pollution level by greenhouse gases CO, CO2, NH3, NO, PM2. 5, PM10, real-time transmission of the collected data to the data processing server, real-time processing and analysis of the received data using various analytical methods, visualization of the air quality monitoring results in the form of a city map with n districts displaying all air parameters. The user can select the air parameters of interest in the mobile application of the cyber-physical system. After selecting such parameters, the visualization of the air quality monitoring results is adapted to the user's needs: the measured value of the parameter selected by the user is displayed on the image of the district on the city map, and the mobile application displays a sound signal in the background and a flashing sign on the image of the district on the city map in the application, which signals a danger in this area of the city; clicking on this sign displays a notification on the screen about the indicator for which there is a danger and recommendations for protecting the health of residents in this case.