This study develops a modelling framework for activity concentration prediction following a Machine Learning (ML) approach. The study aims to understand the spatial and temporal evolution of activity ...considering the effects of the built environment, time of day, and past activities. This study utilizes the Nova Scotia Travel Activity (NovaTRAC) survey and Info Canada Business Establishment dataset to extract activity and built environment information. An Artificial Neural Network (ANN) modelling approach is adopted for prediction modelling as it provides advantages over other modelling approaches in dealing with assumptions, non-linearity, and model accuracy. The ANN model is trained and validated through a trial-and-error process using various model architectures and evaluation metrices, such as mean square error (MSE) and mean absolute error (MAE). Results show that model fitness is satisfactory with significantly smaller values of MSE (0.37) and MAE (0.23). Furthermore, results indicate high prediction accuracy. The outcomes of this study provide insights into factors affecting activity density which will further aid in designing public spaces, transportation infrastructures and safety protocols.
Globally rates of active school travel (AST) are in decline. New Zealand has one of the lowest rates of AST compared to other countries. To date much research investigating reasons for this decline ...and evaluations of interventions to increase the uptake of AST have occurred from an adult-centric perspective. This study takes a child-centred approach to elicit children's voice in understanding school travel perceptions and preferences. In total 1102 children aged 8-13 years from 19 schools across Auckland, New Zealand took part in a public participation GIS survey utilising both closed- and open-ended questions. The results indicate that regardless of active or passive travel mode, children are aware of the distance/time to school and enjoy the opportunity for social interactions. An evidence-based framework for understanding and measuring children's likes, dislikes, and key activities for their route to school is presented.
Celotno besedilo
Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
The accumulation of artificially built environment stock during urbanization processes has been actively involved in altering the material and energy use pattern of human societies. Therefore, an ...accurate assessment of built environment stock can provide insights for decision makers to implement appropriate environmentally sustainable retrofitting strategies. This study presents a building stock estimation enhancement framework (BSEEF) that leverages nighttime light (NTL) to accurately assess and spatially map building stocks. By innovatively integrating a region classification module with a hybrid region-specified self-optimization module, BSEEF adaptively enhances the estimation accuracy across diverse urban landscapes. A comparative case study of Japan demonstrated that BSEEF significantly outperformed a traditional linear regression model, with improvements ranging from 1.81% to 16.75% across different metrics used for assessment, providing more accurate building stock estimates. BSEEF enhances environment/sustainability studies by enabling precise spatial analysis of built environment stocks, offering a versatile and robust framework that adapts to technological changes and achieves superior accuracy without extensive reliance on complex datasets. These advances will make BSEEF an indispensable tool in strategic planning for urban development, promoting sustainable and resilient communities globally.
Fast and accurate airflow simulations in the built environment are critical to provide acceptable thermal comfort and air quality to the occupants. Computational Fluid Dynamics (CFD) offers detailed ...analysis on airflow motion, heat transfer, and contaminant transport in indoor environment, as well as wind flow and pollution dispersion around buildings in urban environments. However, CFD still faces many challenges mainly in terms of computational expensiveness and accuracy. With the increasing availability of large amount of data, data driven models are starting to be investigated to either replace, improve, or aid CFD simulations. More specifically, the abilities of deep learning and Artificial Neural Networks (ANN) as universal non-linear approximator, handling of high dimensionality fields, and computational inexpensiveness are very appealing. In built environment research, deep learning applications to airflow simulations shows the ANN as surrogate, replacement for expensive CFD analysis. Surrogate modeling enables fast or even real-time predictions, but usually at a cost of a degraded accuracy. The objective of this work is to critically review deep learning interactions with fluid mechanics simulations in general, to propose and inform about different techniques other than surrogate modeling for built environment applications. The literature review shows that ANNs can enhance the turbulence model in various way for coupled CFD simulations of higher accuracy, improve the efficiency of Proper Orthogonal Decomposition (POD) methods, leverage crucial physical properties and information with physics informed deep learning modeling, and even unlock new advanced methods for flow analysis such as super-resolution techniques. These promising methods are largely yet to be explored in the built environment scene. Unavoidably, deep learning models also presents challenges such as the availability of consistent large flow databases, the extrapolation task problem, and over-fitting, etc.
•In built environment ANN are only used as surrogate model for expensive CFD analysis.•New potential methods are physics informing, turbulence enhancement, super-resolution.•Challenges are the availability of large databases, extrapolation and over-fitting.
Human mobility is attracting more attention in public health research; however, the existing paradigms typically lack a universal indicator to reveal the underlying mechanism for both urban and rural ...cases. Based on the large-scale datasets, including national survey, census, and billions of GPS trajectories, we found that the preference for choosing vehicles for travel can be a powerful and universal indicator for regional health levels. Firstly, we showed reliable evidence on the correlation among travel environment, travel behaviors, and health level. Then, we proposed a new travel inverse preference index that is a reliable measurement of unhealthy lifestyle levels and the age-corrected mortality rates within a particular region. The result further showed that multiple spatial environment factors, such as urbanization level, climates, and local walkability, are also strongly related to the indicator. Additionally, we conducted a comprehensive spatial analysis to develop strategic policies that the government could adopt for potential social improvement.
•Based on billions of GPS trajectories, we found vehicle travel preference is a universal indicator for regional health level.•The relationship between travel preference and unhealthy lifestyle level is the key to connect human mobility and health.•Travel inverse preference index is proven to be a better indicator to represent the social trend of travel mode preference.
One strategy for increasing physical activity is to create and enhance access to park space. We assessed the literature on the relationship of parks and objectively measured physical activity in ...population-based studies in the United States (US) and identified limitations in current built environment and physical activity measurement and reporting. Five English-language scholarly databases were queried using standardized search terms. Abstracts were screened for the following inclusion criteria: 1) published between January 1990 and June 2013; 2) US-based with a sample size greater than 100 individuals; 3) included built environment measures related to parks or trails; and 4) included objectively measured physical activity as an outcome. Following initial screening for inclusion by two independent raters, articles were abstracted into a database. Of 10,949 abstracts screened, 20 articles met the inclusion criteria. Five articles reported a significant positive association between parks and physical activity. Nine studies found no association, and six studies had mixed findings. Our review found that even among studies with objectively measured physical activity, the association between access to parks and physical activity varied between studies, possibly due to heterogeneity of exposure measurement. Self-reported (vs. independently-measured) neighborhood park environment characteristics and smaller (vs. larger) buffer sizes were more predictive of physical activity. We recommend strategies for further research, employing standardized reporting and innovative study designs to better understand the relationship of parks and physical activity.
•We reviewed research on parks and objectively measured physical activity.•Measurement and reporting of park density and proximity is not standardized.•The association of parks and physical activity was inconsistent across studies.•Standardized measurement and reporting are needed for future meta-analyses.
Abstract
Background and Objectives
The physical environment in long-term care facilities has an important role in the care of residents with dementia. This paper presents a literature review focusing ...on recent empirical research in this area and situates the research with therapeutic goals related to the physical environment.
Research Design and Methods
A comprehensive literature search was conducted in Ageline, PsychINFO, CINAHL, Medline and Google Scholar databases to identify relevant articles. A narrative approach was used to review the literature.
Results
A total of 103 full-text items were reviewed, including 94 empirical studies and 9 reviews. There is substantial evidence on the influence of unit size, spatial layout, homelike character, sensory stimulation, and environmental characteristics of social spaces on residents’ behaviors and well-being in care facilities. However, research in this area is primarily cross-sectional and based on relatively small and homogenous samples.
Discussion and Implications
Given the increasing body of empirical evidence, greater recognition is warranted for creating physical environments appropriate and responsive to residents’ cognitive abilities and functioning. Future research needs to place greater emphasis on environmental intervention-based studies, diverse sample populations, inclusion of residents in different stages and with multiple types of dementia, and on longitudinal study design.
In studies of the effect of built environment on travel behaviour, residential self-selection is an increasingly important issue. Self-selection implies that households locate in places that provide ...them with conducive conditions for their preferred way of travelling. In these studies, it is assumed that attitudes toward different travel modes are an important factor in location choice, and that households are unconstrained in choosing their preferred residential location. This paper challenges these assumptions, by distinguishing between the more passive travel attitude and travel considerations as a deliberate reason to locate in a certain place. Based on a survey among 355 recently relocated households in Dutch TOD locations, we find that the association between travel attitude and residential environment is weak, and that the association between travel attitude and travel as a factor in location choice is moderate at best. Multivariate models show that both travel attitude and travel being a reason for location choice influence travel mode use, suggesting that travel attitude is insufficient to fully reflect self-selection processes. In comparison to other travel modes, train travel is most influenced by the fact whether residents deliberately chose to live in an environment conducive to using this mode.
Simple design and easy power generation are the two main factors that make the use of vertical axis wind turbines affordable in small scale applications. But, their low efficiency prevents their ...commercialization. Augmentation techniques can increase the generated power by accelerating the wind speed on the turbine. The present study employs high-fidelity numerical modeling to investigate several important parameters of a flanged diffuser called “wind-lens” installed on a Savonius wind turbine. Six geometrical parameters of the wind-lens including tip clearance, nozzle length, diffuser length, flange length, nozzle opening angle, and diffuser opening angle are studied. Moreover, the sensitivity of the wind-lens to the wind direction is evaluated over a wide range of yaw angles. By using the flow field around the wind-lens, an attempt is made to better understand the effect of each parameter on the turbine performance. Finally, an optimal wind-lens configuration for the Savonius wind turbine is proposed. The optimized wind-lens configuration contributes Cp,max = 0.702 at λ = 1 which exceeds the Betz limit. Also, it reduces the torque ripple factor range from 2<TRFopen turbine<9 to 1<TRFoptimal configuration<2. Therefore, the proposed system can be considered a feasible and cost-effective design for power generation, especially in the built environment.
•A wind-lens configuration is proposed for the Savonius wind turbine.•The Betz limit is exceeded by using the proposed optimal wind lens.•The power coefficient is improved by a factor of 3.25 through an optimized wind-lens.•The torque ripple factor is evaluated for the proposed system.•The effect of yaw angles on turbine performance is studied.
The construction and real estate industry is, directly and indirectly, responsible for circa 40% of global greenhouse gas (GHG) emissions. Therefore, it is relevant to look upon the building sector ...as a focus area for a transition from Linear Economy to Circular Economy (CE), as outlined by the EU Commission through European Green Deal as a growth strategy for EU and, as a consequence of this, the EU Circular Economy Action Plan. This article aims to analyse current knowledge and methodologies for integrating life cycle thinking, namely Life Cycle Assessment (LCA), Life Cycle Costing (LCC), and Social Life Cycle Assessment (S-LCA) into Life Cycle Sustainability Assessment (LCSA), as an integrated assessment methodology, that can support the transition of the construction and real estate industry to a circular economy. We conducted a literature review to address this effort, including forty-two articles, thirteen of which report on integrating all three methods. Furthermore, we analysed the content of these articles and identified knowledge gaps in this area. Conclusions are, that for CE to succeed, a comprehensive and circular view upon buildings' life cycle phases is necessary to give closer attention to the service life phase and the reuse/recycle phase of buildings. Such attention will impact the building's value chain, regarding the involvement of more stakeholders, not only in the early phases of project development (decision-making) but particularly in the design phase; Further research in evaluating CE through the integration of life LCA, LCC and S-LCA into LCSA is necessary to support the transition; For this purpose, S-LCA needs even further maturation and development, as S-LCA will, through focus and development, become an essential lever for raising attention focused upon the use phase and the reuse/recycle phase; A specific focus upon making integrated life cycle sustainability assessment operational and useable for practitioners in the building processes is necessary.
•Existing standards for assessing the life cycles of complex buildings and refurbishments are challenged in a circular economy perspective.•Further research integrating LCA, LCC and S-LCA into LCSA is necessary to support the transition to a circular economy for the construction and real estate industry.•The use phase, recycling/reuse phase, and repurpose phase of buildings' service lives are underexposed in existing methodologies for LCSA, LCA, LCC and S-LCA.•S-LCA can become an essential lever for the transition to a circular economy in the construction and real estate business.•S-LCA needs further maturation to support the transition to a circular economy in the construction, and indicators need to be tailored specifically to the building sector.