Search

Two elements g, h of a permutation group G acting on a set V are said to be intersecting if g (v) = h (v) for some v ∈ V . More generally, a subset F of G is an intersecting set if every pair of elements of F is intersecting. The intersection density ρ (G) of a transitive permutation group G is the maximum value of the quotient | F | / | G v | where F runs over all intersecting sets in G and G v is the stabilizer of v ∈ V . A vertex-transitive graph X is intersection density stable if any two transitive subgroups of Aut (X) have the same intersection density. This paper studies the above concepts in the context of cubic symmetric graphs. While a 1-regular cubic symmetric graph is necessarily intersection density stable, the situation for 2-arc-regular cubic symmetric graphs is more complex. A necessary condition for a 2-arc-regular cubic symmetric graph admitting a 1-arc-regular subgroup of automorphisms to be intersection density stable is given, and an infinite family of such graphs is constructed. [ABSTRACT FROM AUTHOR]

A subset F of a finite transitive group G ≤ Sym (Ω) is intersecting if any two elements of F agree on an element of Ω. The intersection density of G is the number ρ (G) = max ⁡ { | F | / | G ω | | F ⊂ G is intersecting } , where ω ∈ Ω and G ω is the stabilizer of ω in G. It is known that if G ≤ Sym (Ω) is an imprimitive group of degree a product of two odd primes p > q admitting a block of size p or two complete block systems, whose blocks are of size q , then ρ (G) = 1. In this paper, we analyze the intersection density of imprimitive groups of degree pq with a unique block system with blocks of size q based on the kernel of the induced action on blocks. For those whose kernels are non-trivial, it is proved that the intersection density is larger than 1 whenever there exists a cyclic code C with parameters [ p , k ] q such that any codeword of C has weight at most p − 1 , and under some additional conditions on the cyclic code, it is a proper rational number. For those that are quasiprimitive, we reduce the cases to almost simple groups containing Alt (5) or a projective special linear group. We give some examples where the latter has intersection density equal to 1, under some restrictions on p and q. [ABSTRACT FROM AUTHOR]

Physical activity supportive environments have the potential to promote health-related fitness in adults. However, the extent to which neighbourhood built characteristics promote health-related fitness via physical activity has received little research attention. Therefore, our objective was to estimate the indirect and direct effects between neighbourhood built characteristics and health-related fitness mediated by physical activity. Using cross-sectional data collected between 2014 and 2019, we merged neighbourhood built characteristics, physical activity, and health-related fitness variables, derived from two Canadian national databases. Using these data, we estimated sex-stratified covariate-adjusted path models (males: n = 983 to 2796 and females: n = 962 to 2835) to assess if accelerometer-measured light, moderate, and vigorous intensity physical activity mediated associations between objectively measured neighbourhood built characteristics (intersection density, dwelling density, points of interest, and transit density) and health-related fitness (grip strength, jump height, V ̇ O 2 max , and flexibility). Across 16 sex-specific models, we estimated 48 indirect and 16 direct effects. Concerning significant associations, for males we found that 16.6% of indirect and 18.8% of direct were negative and 4.2% of indirect and 0% of direct were positive. For females, we found that 12.5% of indirect and 0% of direct were negative and 0% of indirect and 25% of direct effects were positive. Individual Canadian Active Living Environment built characteristics are positively associated with moderate-intensity physical activity and negatively associated with light-intensity physical activity. Further, associations between activity friendly neighbourhood characteristics and health related-fitness may be distinct from physical activity. • Built characteristics (BCs) and health-related fitness (HRF) were related (BC-HRF). • Direct effects were found between BCs and grip strength in males. • Direct effects were found between BCs, V ̇ O 2 max , and flexibility in females. • BC-HRF associations varied by type of BC, activity intensity, and component of HRF. [ABSTRACT FROM AUTHOR]

With the aim of maintaining a decent level of accessibility, the presence of intersections, often in high numbers, is one of the typical features of rural roads. However, evidence from literature shows that increasing intersection density increases the risk of accidents. Accident analysis literature regarding intersection density primarily consists of accident prediction models which are a useful tool for measuring safety performance of roads, but the literature is lacking in terms of evaluation of driver behavior using direct measurements of driver performance. This study focuses on the influence of intersection density on the risk perception of drivers through experiments carried out with a driving simulator. A virtual driving environment of a rural roadway was constructed. The road consisted of segments featuring extra-urban and village driving environments with varying intersection density level. Participants were recruited to drive through this virtual driving environment. Various driver performance measures such as vehicle speed and brake and gas pedal usage were collected from the experiment and then processed for further analysis. Results indicate an increase in driver's perceived risk when the intersection density increased, according with the findings from the accident prediction modeling literature. However, at the same time, this driving simulator study revealed some interesting insights about oscillating perceived risk among drivers in the case of mid-level intersection separation distances. Beyond the accident research domain, findings from this study can also be useful for engineers and transportation agencies associated with access management to make more informed decisions. [ABSTRACT FROM AUTHOR]

INTRODUCTION: There are several online mapping systems like Google Maps, Waze, Here, Apple Maps, Bing Maps, etc. which are developed to visualize real-time traffic conditions which rely on crowdsourced GPS trails; obtained from worldwide smartphone users. Such systems still suffer from some limitations like a) inadequate traffic information in suburban cities and rural zones, b) system failure to infer the proper reasons for slow traffic state, c) difficulties in the extraction of raw traffic data for further development of any customized application. Significant spatio-temporal similarity patterns are observed in city traffic behavior unless there are some exceptional events like any disaster, VIP visit, international cricket match or bad weather condition, etc. OBJECTIVES: Designing a framework and developing a system which enables collection of raw sensor information from users and to identify a model to generate a speed profile of city roads using historical logs as well as to infer the context of slow traffic based on ambient subjective road features and to provide map visualization. METHODS: We have used road surface quality, density of vehicles, type of neighborhood and road geometry for developing speed profile for a particular road segment. We have carried out the experiments on different classification algorithms like, K-nearest Neighbor(KNN), Decision Tree(DT), Random Forest(RF) and Gradient Boost(GB) with necessary tuning of parameters. RESULTS: GB outperforms other classification algorithms in estimating the speed class of road segments among all classifier algorithms with highest F1- Score of 0.8345. A fair driver rating system which can be derived from our results. CONCLUSION: The results obtained from the proposed novel framework provide a proof of concept that speed profiles may be successfully derived from ambient road features even when sample space is sparse. [ABSTRACT FROM AUTHOR]

INTRODUCTION: There are several online mapping systems like Google Maps, Waze, Here, Apple Maps, Bing Maps, etc. which are developed to visualize real-time traffic conditions which rely on crowdsourced GPS trails; obtained from worldwide smartphone users. Such systems still suffer from some limitations like a) inadequate traffic information in suburban cities and rural zones, b) system failure to infer the proper reasons for slow traffic state, c) difficulties in the extraction of raw traffic data for further development of any customized application. Significant spatio-temporal similarity patterns are observed in city traffic behavior unless there are some exceptional events like any disaster, VIP visit, international cricket match or bad weather condition, etc. OBJECTIVES: Designing a framework and developing a system which enables collection of raw sensor information from users and to identify a model to generate a speed profile of city roads using historical logs as well as to infer the context of slow traffic based on ambient subjective road features and to provide map visualization. METHODS: We have used road surface quality, density of vehicles, type of neighborhood and road geometry for developing speed profile for a particular road segment. We have carried out the experiments on different classification algorithms like, K-nearest Neighbor(KNN), Decision Tree(DT), Random Forest(RF) and Gradient Boost(GB) with necessary tuning of parameters. RESULTS: GB outperforms other classification algorithms in estimating the speed class of road segments among all classifier algorithms with highest F1- Score of 0.8345. A fair driver rating system which can be derived from our results. CONCLUSION: The results obtained from the proposed novel framework provide a proof of concept that speed profiles may be successfully derived from ambient road features even when sample space is sparse.

The land-use mix observed in the smaller Indian cities is peculiar, and in this context there were no past studies on how the landuse mix influences the travel pattern. The existing indices used for quantifying the land-use mix were found to have limitations in capturing the characteristics of land-use mix observed in the smaller Indian cities. The present study analyzed the drawbacks and limitations of the existing indices and modified the dissimilarity and entropy indices, as well as formulated new indices suitable to quantify the mixed land use. The objectives behind the mix quantification were to capture the land-use balance, land-use mix, and land-use complementarity. The modified dissimilarity and entropy indices were found to be significant in explaining the variation in the trip lengths as well as preference toward nonmotorized transport (NMT). Proposed new parameters such as the area index and mix-type index were found to be significant in explaining the variability observed in the trip length and the nonmotorized mode choice. From the elasticity analysis it has been observed that a slight change in the land-use mix significantly affects the travel patterns. Further, from the estimated multinomial logit (MNL) models it has been observed that the mixed land-use parameter was found to be significant in explaining the choice of public transport and nonmotorized modes. [ABSTRACT FROM AUTHOR]

The concept of street connectivity has been gaining increasing appeal among researchers, planners, and planning authorities. In response, many connectivity metrics have been developed in an effort to understand better street network connectivity. This paper will study the effectiveness and consistency of three mainstream metrics – the Connectivity Index, Intersection Density, and Street Density – with respect to differences in study area and geometry. While these metrics are intended to be applied incrementally, this paper reveals that the metrics often fail to do this successfully. By controlling for many variables – including block size, block geometry, right-of-way size, network size, and network geometry – actual behaviors of these metrics deviate substantially from their intended behaviors. The metrics are non-linear functions of both study area and geometry and are ultimately inconsistent and unpredictable. In other words, each metric will yield inconsistent readings based upon the amount of area studied or the arrangement of the study boundary drawn. This has two major consequences: (1) the metrics will not produce the results desired as they are applied to incremental development; and (2) the metrics can be easily gamed by a developer privy to the information found within this paper. Neither of these outcomes is desirable in helping to better understand and potentially regulate street connectivity. [ABSTRACT FROM AUTHOR]

Analysis of the connectivity of a fracture network is an important component of the design, assessment and development of fracture-based reservoirs in geothermal, petroleum and groundwater resource applications. It is a useful means of characterising the flow pathways and the mechanical behaviours of reservoirs. An appropriate practical measure is required for connectivity characterisation because of the extreme complexity of fracture networks. In this paper, we propose the connectivity field (CF), as a useful measure to evaluate the spatial connectivity characteristics of fractures in a fracture network. The CF can be applied on both a particular realisation of a fracture network model (for deterministic evaluation) and on stochastic fracture network models using stochastic modelling and Monte Carlo simulations (for probabilistic evaluation with uncertainties). Two extensions are also proposed: the generalised connectivity field, a measure that is independent of support size, and the probabilistic connectivity field. Potential applications of the CF and its extensions are in determining the optimal location of an injection or production well so as to maximise reservoir performance and in determining potential flow pathways in fracture networks. The average CF map shows strong correlations with the $$X_{\mathrm{f}}$$ and P21 measures. The relationships between the CF measures, the fracture intersection density and the fracture network connectivity index are also investigated. [ABSTRACT FROM AUTHOR]

The objective of this work is to develop a new and easily computable measure of pedestrian friendliness for urban neighborhoods that makes the best use of the available data and also addresses the issues concerning other models in use. The Pedestrian Environment Index (PEI) is defined as the product of four components representing land-use diversity (based on the concept of entropy), population density, commercial density, and intersection density. The final PEI is bound between 0 and 1, and uses data that typically are readily available to planners and metropolitan planning organizations (MPO). The results of this method are region-specific; they are comparable only between the zones within the given study area. As a case study, the city of Chicago is analyzed at the sub-traffic analysis zone (sub-TAZ) level. The results agree closely with the expectation of pedestrian friendliness across different parts of the city. Possible extensions are also listed, including a further study to determine statistical relationships between the PEI and common socio-economic characteristics. The method could also be further improved should more types of data become available. [ABSTRACT FROM AUTHOR]

Abstract: We prove inequalities for mixed volumes of zonoids with isotropic generating measures. A special case is an inequality for zonoids that is reverse to the generalized Urysohn inequality, between mean width and another intrinsic volume; here the equality case characterizes parallelepipeds. We apply this to a question from stochastic geometry. It is known that among the stationary Poisson hyperplane processes of given positive intensity in n-dimensional Euclidean space, the ones with rotation invariant distribution are characterized by the fact that they yield, for , the maximal intensity of the intersection process of order k. We show that, if the kth intersection density is measured in an affine-invariant way, the processes of hyperplanes with only n fixed directions are characterized by a corresponding minimum property. [Copyright &y& Elsevier]

Two elements g and h of a permutation group G acting on a set V are said to be intersecting if g (v) = h (v) for some v ∈ V. More generally, a subset F of G is an intersecting set if every pair of elements of F is intersecting. The intersection density ρ (G) of a transitive permutation group G is the maximum value of the quotient | F | / | G v | where G v is the stabilizer of v ∈ V and F runs over all intersecting sets in G. Intersection densities of transitive groups of degree pq , where p > q are odd primes, is considered. In particular, the conjecture that the intersection density of every such group is equal to 1 (posed in Meagher et al. (2021) [15]) is disproved by constructing a family of imprimitive permutation groups of degree pq (with blocks of size q), where p = (q k − 1) / (q − 1) , whose intersection density is equal to q. The construction depends heavily on certain equidistant cyclic codes [ p , k ] q over the field F q whose codewords have Hamming weight strictly smaller than p. [ABSTRACT FROM AUTHOR]

Objectives: To study the extent to which home-to-school distance and neighbourhood walkability were associated with self-reported active travel to school (ATS) (eg, walking, cycling), and to explore how distance moderates the effect of walkability on ATS, among 10-11 years old., Design: Cross-sectional study., Setting: Data were collected between May 2015 and May 2016 in partnership with the Growing Up in Scotland Study, a nationally representative longitudinal cohort study., Participants: 713 children (male (n=330) and female (n=383) 10-11 years old) from Studying Physical Activity in Children's Environments across Scotland., Primary and Secondary Outcome Measures: Children who actively travelled to/from school categorised as active all (100% of ATS) and active 60%+ (at least 60% of ATS); home-to-school road/path network distance (<0.5 km, 0.5 to <1 km, 1 to <1.5 km, 1.5 to <2 km, 2 km+); home neighbourhood walkability (i.e., composite measure of road/path intersection density and dwelling density) (in quintiles)., Results: Distance and walkability were both associated with ATS. The likelihood of ATS for all or most journeys decreased with increasing distance. Compared with 'most' walkable areas (Q1), the odds of active all were significantly lower within least walkable areas (Q5 OR 0.45, 95% CI 0.21 to 0.99), and odds of active 60% + were significantly less in Q2-Q5 (lowest odds Q5 OR 0.20, 95% CI 0.07 to 0.47). Regarding walkability and distance interactions, for all distance categories, higher walkability increased the probability of ATS (for most school journeys)., Conclusion: Walkability was positively associated with ATS within all distance categories, with the relationship between walkability and ATS more complex than the clear-cut association between distance and ATS. A more walkable environment had a larger effect on the probability of reaching the 60% threshold of school journeys using ATS than the probability of always travelling in an active manner. Investment is needed in existing less walkable neighbourhoods to provide infrastructure to support opportunities for children's ATS., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY. Published by BMJ.)