Exploring factors related to users’ experience of public transport route choice: influence of context and users profiles

This exploratory study aims to achieve a better understanding of the users-related factors that affect the choice of routes in public transport (PT). We also look at what can motivate route and modes changes towards alternatives in a real situation. We investigated the experience of 19 users of PTs, using the critical incident technique (Flanagan in Psychol Bull 51(4):327, 1954). We asked participants to report incidents (i.e. situations) in cases they were very satisfied or dissatisfied with their choice. For both situations, the case of their usual route and case of an alternative were considered. A total of 91 incidents were collected and analysed using a multiple correspondences analysis. Additionally, users’ profiles were characterized and superposed to the analysis of incidents content. The main results are as follows. First, the user’s choice of PT route depends on the context (i.e. aim of the travel, time of day). Second, taking an alternative to the usual PT route or using a route combining different transport modes is determined by the context and by factors related to the pleasantness of the travel (e.g. to accompany a friend along the travel). Finally, depending on the user’s profile (i.e. combination of attitude towards PT and demographic variables), the factors taken into account to make the choice of a PT route are related to the efficiency or the pleasantness of the trip. These results show the importance of the contextual factors and the users’ profiles in route choice. They suggest that these factors should be further taken into account in new tools and services for mobility.     

SWGMM: a semi-wrapped Gaussian mixture model for clustering of circular–linear data

Finite mixture models are widely used to perform model-based clustering of multivariate data sets. Most of the existing mixture models work with linear data; whereas, real-life applications may involve multivariate data having both circular and linear characteristics. No existing mixture models can accommodate such correlated circular–linear data. In this paper, we consider designing a mixture model for multivariate data having one circular variable. In order to construct a circular–linear joint distribution with proper inclusion of correlation terms, we use the semi-wrapped Gaussian distribution. Further, we construct a mixture model (termed SWGMM) of such joint distributions. This mixture model is capable of approximating the distribution of multi-modal circular–linear data. An unsupervised learning of the mixture parameters is proposed based on expectation maximization method. Clustering is performed using maximum a posteriori criterion. To evaluate the performance of SWGMM, we choose the task of color image segmentation in LCH space. We present comprehensive results and compare SWGMM with existing methods. Our study reveals that the proposed mixture model outperforms the other methods in most cases.     

Statistical shape modelling for expression-invariant face analysis and recognition

Paper introduces a 3-D shape representation scheme for automatic face analysis and identification, and demonstrates its invariance to facial expression. The core of this scheme lies on the combination of statistical shape modelling and non-rigid deformation matching. While the former matches 3-D faces with facial expression, the latter provides a low-dimensional feature vector that controls the deformation of model for matching the shape of new input, thereby enabling robust identification of 3-D faces. The proposed scheme is also able to handle the pose variation without large part of missing data. To assist the establishment of dense point correspondences, a modified free-form-deformation based on B-spline warping is applied with the help of extracted landmarks. The hybrid iterative closest point method is introduced for matching the models and new data. The feasibility and effectiveness of the proposed method was investigated using standard publicly available Gavab and BU-3DFE datasets, which contain faces with expression and pose changes. The performance of the system was compared with that of nine benchmark approaches. The experimental results demonstrate that the proposed scheme provides a competitive solution for face recognition.     

A Model of Green Acceptance and Intentions to Use Bike-Sharing: YouBike Users in Taiwan

With the emphasis on sustainability in transportation, bike-sharing systems are gaining popularity. This paper investigates the attitudes of users of a bike-sharing system with the aim of identifying their priorities, thus allowing local governments to focus their efforts most effectively on enhancing users’ intentions to use such systems. The relationships among green perceived usefulness (the extent to which individuals believe that a bike-sharing system will improve the environmental performance of some part of their life within a specific context), user attitude and perceived ease of use with green intentions, and the mediation effect of user attitude towards bike-sharing are explored. The focus of the study is on how to enhance green intentions via perceived usefulness, perceived ease of use and user attitude of the green technology acceptance model (green TAM) (Davis 1989). The two-step approach of structural equation modeling was applied to analyze the empirical results, which indicated that green perceived usefulness and user attitude have positive influences on the green intentions of 262 users and 262 non-users from ten sampled bike-sharing sites around the central administrative districts of Taipei. However, user attitude has the highest mediation effect on green intentions, and perceived ease of use does not have a significant effect on intentions for either users or non-users. Therefore, governmental institutions can strive to improve the attitudes of bike-sharing users and non-users, their green perceived usefulness, and perceived ease of use to strengthen their intentions to use this mode of sustainable transportation.     

Competition and Cooperation in a Bidding Model of Electrical Energy Trade

A cooperative game-theoretic framework is introduced to study the behavior of cooperating and competing electrical-energy providers in the wholesale market considering price-preference rational consumers. We study the physical and economic aspects of the power transmission system operation focussing on the incentives for group formation. We analyze the interactions of generators in an idealized environment described by a DC load flow model where the network is lossless and is operated by an independent network operator who ensures network stability and fulfillment of consumption needs while taking into account the preferences of consumers over generators. We show that cooperation of generators may be necessary to divert consumers from their previous providers. In the second part of the paper we assume an iterative process in which the generators publish their price offers simultaneously, based on which the consumers preferences are determined. We study the dynamics of the prices and profits as the system evolves in time while each coalition is trying to maximize its expected profit in each step. The model deals with network congestion and n ? 1 line-contingency reliability as not every generator-consumer matching is allowed to ensure the safe operation of the transmission system. The profit of the generators is determined as the difference between their income and their production cost, which is a quadratic concave function of the production amount. Any non-monopolistic proper subset of the generators may cooperate and harmonize their offered prices to increase their resulting profit. Since we allow the redistribution of profits among cooperating generators, a transferable-utility game-theoretic framework is used. Furthermore, as cooperation affects the outsiders as well, the resulting game is defined in partition function form. The model is able to demonstrate some interesting benefits of cooperation as well as the effect of market regulations and asymmetric information on the resulting profits and total social cost.     

<Emphasis Type="Italic">Melodie di pietra</Emphasis> by Adriana Rossi

In Melodie di pietre, Adriana Rossi has produced an in-depth analysis of the cloister of San Cugat on the basis of musical notions and symbolism. This provides us with an occasion for some brief reflections on the historic relationships between music and architecture.     

Privacy Preserving Geo-Linkage in the Big Urban Data Era

Big data technologies and a range of Government open data initiatives provide the basis for discovering new insights into cities; how they are planned, how they managed and the day-to-day challenges they face in health, transport and changing population profiles. The Australian Urban Research Infrastructure Network (AURIN – www.aurin.org.au) project is one example of such a big data initiative that is currently running across Australia. AURIN provides a single gateway providing online (live) programmatic access to over 2000 data sets from over 70 major and typically definitive data-driven organizations across federal and State government, across industry and across academia. However whilst open (public) data is useful to bring data-driven intelligence to cities, more often than not, it is the data that is not-publicly accessible that is essential to understand city challenges and needs. Such sensitive (unit-level) data has unique requirements on access and usage to meet the privacy and confidentiality demands of the associated organizations. In this paper we highlight a novel geo-privacy supporting solution implemented as part of the AURIN project that provides seamless and secure access to individual (unit-level) data from the Department of Health in Victoria. We illustrate this solution across a range of typical city challenges in localized contexts around Melbourne. We show how unit level data can be combined with other data in a privacy-protecting manner. Unlike other secure data access and usage solutions that have been developed/deployed, the AURIN solution allows any researcher to access and use the data in a manner that meets all of the associated privacy and confidentiality concerns, without obliging them to obtain ethical approval or any other hurdles that are normally put in place on access to and use of sensitive data. This provides a paradigm shift in secure access to sensitive data with geospatial content.     

Yang–Baxter equations and quantum entanglements

In this paper some results associated with a new type of Yang–Baxter equation (YBE) are reviewed. The braiding matrix of Kauffman–Lomonaco has been extended to the solution (called type-II) of Yang–Baxter equation (YBE) and the related chain Hamiltonian is given. The Lorentz additivity for spectral parameters is found, rather than the Galilean rule for the familiar solutions (called type-I) of YBE associated with the usually exact solvable models. Based on the topological basis, the N-dimensional solution of YBE is found to be the Wigner D-functions. The explicit examples for spin-\(\frac{1}{2}\) and spin-1 have been shown. The extremes of \(\ell _1\)-norm of \(D\)-functions are introduced to distinguish the type-I from type-II of braiding matrices that also correspond to those of von Neumann entropy for quantum information.