ALF-Score+ - Personalization of a Predictive Network-Based Walkability Scoring System

2021 ◽  
Author(s):  
Ali M. S. Alfosool ◽  
Daniel Fuller ◽  
Yuanzhu Chen
Keyword(s):  
Road Network ◽  
Strong Association ◽  
Social Environments ◽  
Points Of Interest ◽  
Novel Approach ◽  
System P ◽  
Single Score ◽  
Cluster Profiles ◽  
Us Cities ◽  
Feature Score

Measuring environments around us (cities, roads, social environments) is crucial to understand human behaviour and help predict how aspects of environment influence behaviour and health. Walkability is one measure of environment used to predict health. Walkability combines aspects of environment (population, roads, amenities) into a single score. Existing measures are often one-size-fits-all with very limited personalization. In our previous work, we defined Active Living Feature Score, ALF-Score, a novel approach to measure network-based walkability. ALF-Score uses road network structures and points of interest to generate models capable of estimating walkability for any point on map. One of ALF-Score's contributions was the inclusion of user opinions to partially address the different perception among individuals and help derive a more personalized walkability score. Here, we take this personalization much further by introducing ALF-Score+ which uses individual user demographics (age, gender, ...) grouped using k-means and t-distributed stochastic neighbor embedding to create clusters based on individuals’ demographic characteristics. Each cluster is treated as a single profile representing a subset of users. Cluster profiles are added into our pipelines to generate profile-specific network-based walkability models. Results show strong variability among scores generated for each cluster profile with a clear variation in walkability generated for different users within same clusters. ALF-Score+ maintains an accuracy of 90.48% on average showing improvement compared to ALF-Score. We found strong association between cluster profiles' demographics and their scores. ALF-Score+ shows promising results providing personalized walkability based on cluster profiles, instead of a one-size-fits-all approach used by other walkability measures.

scholarly journals ALF-Score - a Novel Approach to Build a Predictive Network-Based Walkability Scoring System

2021 ◽  
Author(s):  
Ali M. S. Alfosool ◽  
Yuanzhu Chen ◽  
Daniel Fuller
Keyword(s):  
Spatial Resolution ◽  
Road Network ◽  
High Spatial Resolution ◽  
Ground Truth ◽  
High Confidence ◽  
The Road ◽  
Points Of Interest ◽  
Novel Approach ◽  
Novel Method ◽  
Feature Score

Abstract Walkability is a term that describes various aspects of the built and social environment and has been associated with physical activity and public health. Walkability is subjective and although multiple definitions of walkability exist, there is no single agreed upon definition. Road networks are integral parts of mobility and should be an important part of walkability. However, using the road structure as nodes is not widely discussed in existing methods. Most walkability measures only provide area-based scores with low spatial resolution, have a one-size-fits-all approach, and do not consider individuals opinion. Active Living Feature Score (ALF-Score) is a network-based walkability measure that incorporates road network structures as a core component. It also utilizes user opinion to build a high-confidence ground-truth that is used in our machine learning pipeline to generate models capable of estimating walkability. We found combination of network features with road embedding and points of interest features creates a complimentary feature set enabling us to train our models with an accuracy of over 87% while maintaining a conversion consistency of over 98%. Our proposed approach outperforms existing measures by introducing a novel method to estimate walkability scores that are representative of users opinion with a high spatial resolution, for any point on the map.

scholarly journals “It’s Not Too Aggressive”: Key Features of Social Branding Anti-Tobacco Interventions for High-Risk Young Adults

2020 ◽  
pp. 152483992091037 ◽  
Author(s):  
Gabriela Toledo ◽  
Julia McQuoid ◽  
Pamela M. Ling
Keyword(s):  
Young Adults ◽  
High Risk ◽  
Social Environments ◽  
Experience Design ◽  
Key Informants ◽  
Brand Recognition ◽  
Novel Approach ◽  
Tobacco Use Prevention ◽  
Promotional Materials ◽  
Depth Interviews

Purpose. Peer crowd–targeted campaigns are a novel approach to engage high-risk young adults in tobacco use prevention and cessation. We elicited the perspectives of young adult key informants to understand how and why two social branding interventions were effective: (1) “COMMUNE,” designed for “Hipsters” as a movement of artists and musicians against Big Tobacco, and (2) “HAVOC,” designed for “Partiers” as an exclusive, smoke-free clubbing experience. Design. Qualitative study (27 semistructured qualitative phone interviews). Setting. Intervention events held in bars in multiple U.S. cities. Participants: Twenty-seven key informants involved in COMMUNE or HAVOC as organizers (e.g., musicians, event coordinators) or event attendees. Measures. We conducted semistructured, in-depth interviews. Participants described intervention events and features that worked or did not work well. Analysis. We used an inductive-deductive approach to thematically code interview transcripts, integrating concepts from intervention design literature and emergent themes. Results: Participants emphasized the importance of fun, interactive, social environments that encouraged a sense of belonging. Anti-tobacco messaging was subtle and nonjudgmental and resonated with their interests, values, and aesthetics. Young adults who represented the intervention were admired and influential among peers, and intervention promotional materials encouraged brand recognition and social status. Conclusion. Anti-tobacco interventions for high-risk young adults should encourage fun experiences; resonate with their interests, values, and aesthetics; and use subtle, nonjudgmental messaging.

scholarly journals An Underwater Pathfinding Algorithm for Optimised Planning of Survey Dives

2020 ◽  
Vol 12 (23) ◽  
pp. 3974
Author(s):  
Marino Mangeruga ◽  
Alessandro Casavola ◽  
Francesco Pupo ◽  
Fabio Bruno
Keyword(s):  
3D Space ◽  
Use Of Resources ◽  
Points Of Interest ◽  
Novel Approach ◽  
Common Task ◽  
Specific Safety ◽  
The One ◽  
First Time ◽  
Over Time ◽  
Dive Profile

In scientific and technical diving, the survey of unknown or partially unexplored areas is a common task that requires an accurate planning for ensuring the optimal use of resources and the divers’ safety. In particular, in any kind of diving activity, it is essential to foresee the “dive profile” that represents the diver’s exposure to pressure over time, ensuring that the dive plan complies with the specific safety rules that have to be applied in accordance with the diver’s qualification and the environmental conditions. This paper presents a novel approach to dive planning based on an original underwater pathfinding algorithm that computes the best 3D path to follow during the dive in order to be able to maximise the number of points of interest (POIs) visited, while taking into account the safety limitations. The proposed approach, for the first time, considers the morphology of the 3D space in which the dive takes place to compute the best path, taking into account the decompression limits and avoiding the obstacles through the analysis of a 3D map of the site. Moreover, three different cost functions are proposed and evaluated to identify the one that could suit the divers’ needs better.

scholarly journals Efficient cleavage of tertiary amide bonds via radical–polar crossover using a copper(ii) bromide/Selectfluor hybrid system

2020 ◽  
Vol 11 (45) ◽  
pp. 12323-12328
Author(s):  
Zhe Wang ◽  
Akira Matsumoto ◽  
Keiji Maruoka
Keyword(s):  
Hybrid System ◽  
Amide Bonds ◽  
Tertiary Amide ◽  
Novel Approach ◽  
System P ◽  
Tertiary Amides

A novel approach for the efficient cleavage of the amide bonds in tertiary amides is reported.

Institutionalism and Schizophrenia 30 Years on

1992 ◽  
Vol 160 (2) ◽  
pp. 230-241 ◽  
Author(s):  
David A. Curson ◽  
Christos Pantelis ◽  
Jan Ward ◽  
Thomas R. E. Barnes
Keyword(s):  
Mental Hospital ◽  
Social Withdrawal ◽  
Strong Association ◽  
Severity Of Illness ◽  
Assessment Instruments ◽  
Social Environments ◽  
The Social ◽  
Significant Difference ◽  
Schizophrenic Patients ◽  
The Relationship

In their comparison of chronic schizophrenic patients in three British mental hospitals in 1960, Wing and Brown found a strong association between the poverty of the social environment and the severity of ‘clinical poverty’ (blunted affect, poverty of speech, and social withdrawal). Between 1960 and 1968 the social environments of all three hospitals improved and a weak causal relationship between social poverty and clinical poverty was reported in a proportion of patients. Using the same assessment instruments as Wing and Brown, the present study re-examined the relationship between social and clinical poverty in the long-stay schizophrenic population of a fourth British mental hospital in 1990. The association found between social and clinical poverty was much weaker than in 1960. Reluctance on the part of patients to be discharged from the institution was unrelated to length of stay. There was no significant difference in severity of illness between the patients in the present study and those in the earlier study. However, patients in the former group spent more time doing nothing than those in the hospital with the most understimulating environment three decades before, with four-fifths doing nothing for over five hours a day, despite a greatly increased ratio of nurses to patients.

Similarity versus relatedness: A novel approach in extractive Persian document summarisation

2017 ◽  
Vol 44 (3) ◽  
pp. 314-330 ◽  
Author(s):  
Fatemeh Shafiee ◽  
Mehrnoush Shamsfard
Keyword(s):  
Feature Selection ◽  
Semantic Information ◽  
Experimental Results ◽  
Clustering Method ◽  
Persian Language ◽  
Novel Approach ◽  
Automatic Text ◽  
Feature Score ◽  
F Measure ◽  
Selection Phase

Automatic text summarisation is the process of creating a summary from one or more documents by eliminating the details and preserving the worthwhile information. This article presents a single/multi-document summariser using a novel clustering method for creating summaries. First, a feature selection phase is employed. Then, FarsNet, the Persian WordNet, is utilised to extract the semantic information of words. Therefore, the input sentences are categorised into three main clusters: similarity, relatedness and coherency. Each similarity cluster contains similar sentences to its core, while each relatedness cluster contains sentences that are related (but not similar) to its core. The coherency clusters show the sentences that should be kept together to preserve the coherency of the summary. Finally, the centroid of each similarity cluster having the most feature score is added to an empty summary. The summary is enlarged by including related sentences from relatedness clusters and excluding similar sentences to its content iteratively. Coherency clusters are applied to the created summary in the last step. The proposed method has been compared with three known existing text summarisation systems and techniques for the Persian language: FarsiSum, Parsumist and Ijaz. Our proposed method leads to improvement in experimental results on different measurements including precision, recall, F-measure, ROUGE-N and ROUGE-L.

Photocatalytic degradation of phenol by the heterogeneous Fe3O4 nanoparticles and oxalate complex system

RSC Advances ◽  
2014 ◽  
Vol 4 (77) ◽  
pp. 40828-40836 ◽  
Author(s):  
Piao Xu ◽  
Guangming Zeng ◽  
Danlian Huang ◽  
Liang Liu ◽  
Cui Lai ◽  
...  
Keyword(s):  
Complex System ◽  
Photocatalytic Degradation ◽  
Fe3o4 Nanoparticles ◽  
Radical Mechanism ◽  
Phenol Removal ◽  
Oxalate Complex ◽  
Novel Approach ◽  
System P

A novel approach for phenol removal using Fe3O4 nanoparticles and oxalate was proposed via a radical mechanism.

scholarly journals Road Network Evolution in the Urban and Rural United States Since 1900

2021 ◽  
Author(s):  
Keith Burghardt ◽  
Johannes Uhl ◽  
Kristina Lerman ◽  
Stefan Leyk
Keyword(s):  
United States ◽  
Economic Development ◽  
Urban Growth ◽  
Road Network ◽  
Road Networks ◽  
Network Evolution ◽  
Critical Assessment ◽  
Rural Planning ◽  
New Development ◽  
Us Cities

Abstract We examine a key component of human settlements mediating pollution and congestion, as well as economic development: roads and their expansion in cities, towns, and villages. Our analysis of road networks in more than 850 US cities and rural counties since 1900 reveals significant variations in the structure of roads both within cities and across the conterminous US. Despite differences in the evolution of these networks, there are commonalities: newer roads tend to become less grid-like. These results persist across the rural-urban continuum and are therefore not just a product of urban growth. These findings illuminate the need for policies for urban and rural planning including the critical assessment of new development trends.

scholarly journals ALF-Score: Network-Based Walkability

2021 ◽  
Author(s):  
Ali M. S. Alfosool ◽  
Yuanzhu Chen ◽  
Daniel Fuller
Keyword(s):  
Road Network ◽  
Network Science ◽  
Ground Truth ◽  
Network Embedding ◽  
High Confidence ◽  
Core Component ◽  
The Road ◽  
Conceptual Definition ◽  
User Data ◽  
Feature Score

Walkability is a term that describes aspects of the built and social environment. Previous studies have shown that different operationalisations of walkability are associated with physical activity and health. Walkability can be subjective and although multiple operational definitions and walkability measurement exist, there is no single agreed upon conceptual definition. Despite lack of consensus of a walkability definition, typical operational definitions include measures of population density, destinations, and the road network. Network science approaches such centralities and network embedding are missing from existing methods, yet they are integral parts of our mobility and should be an important part of how walkability is measured. Furthermore, most walkability measures have a one-size-fits-all approach and do not take into account individual user’s characteristics or walking preferences. To address some limitations of previous works, we developed the Active Living Feature Score (ALF-Score). ALF-Score is a network-based walkability measure that incorporates the road network structures as a core component. It also utilizes user data to build high-confidence ground truth that are used in conjunction with our machine learning pipeline to generate models capable of estimating walkability scores that address existing gaps in the walkability literature. We find, relying on road structure alone, we are able to train our models to estimate walkability scores with an accuracy of over 86% while maintaining a consistency of over 98% over collected user data. Our proposed approach outperforms existing measures by providing a walkability data at a much higher resolution as well as a user-derived result.

scholarly journals Application of AHP to Road Selection

2020 ◽  
Vol 9 (2) ◽  
pp. 86 ◽  
Author(s):  
Yuan Han ◽  
Zhonghui Wang ◽  
Xiaomin Lu ◽  
Bowei Hu
Keyword(s):  
Decision Making ◽  
Road Network ◽  
Analytic Hierarchy ◽  
Ahp Model ◽  
The Road ◽  
Points Of Interest ◽  
Adaptive Thresholds ◽  
Contextual Characteristics ◽  
Hierarchy Process ◽  
Contextual Characteristic

The analytic hierarchy process (AHP), a decision-making method, allows the relative prioritization and assessment of alternatives under multiple criteria contexts. This method is also well suited for road selection. The method for road selection based on AHP involves four steps: (i) Points of Interest (POIs), the point-like representations of the facilities and habitations in maps, are used to describe and build the contextual characteristic indicator of roads; (ii) form an AHP model of roads with topological, geometrical, and contextual characteristic indicators to calculate their importance; (iii) select roads based on their importance and the adaptive thresholds of their constituent density partitions; and (iv) maintain the global connectivity of the selected network. The generalized result at a scale of 1:200,000 by AHP-based methods better preserved the structure of the original road network compared with other methods. Our method also gives preference to roads with relatively significant contextual characteristics without interfering with the structure of the road network. Furthermore, the result of our method largely agrees with that of the manual method.

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