2,850 research outputs found
Landslide risk management through spatial analysis and stochastic prediction for territorial resilience evaluation
Natural materials, such as soils, are influenced by many factors acting during their formative and evolutionary process: atmospheric agents, erosion and transport phenomena, sedimentation conditions that give soil properties a non-reducible randomness by using sophisticated survey techniques and technologies. This character is reflected not only in spatial variability of properties which differs from point to point, but also in multivariate correlation as a function of reciprocal distance. Cognitive enrichment, offered by the response of soils associated with their intrinsic spatial variability, implies an increase in the evaluative capacity of the contributing causes and potential effects in failure phenomena. Stability analysis of natural slopes is well suited to stochastic treatment of uncertainty which characterized landslide risk. In particular, this study has been applied through a back- analysis procedure to a slope located in Southern Italy that was subject to repeated phenomena of hydrogeological instability (extended for several kilometres in recent years). The back-analysis has been carried out by applying spatial analysis to the controlling factors as well as quantifying the hydrogeological hazard through unbiased estimators. A natural phenomenon, defined as stochastic process characterized by mutually interacting spatial variables, has led to identify the most critical areas, giving reliability to the scenarios and improving the forecasting content. Moreover, the phenomenological characterization allows the optimization of the risk levels to the wide territory involved, supporting decision-making process for intervention priorities as well as the effective allocation of the available resources in social, environmental and economic contexts
A Methodology to Evaluate Accessibility to Bus Stops as a Contribution to Improve Sustainability in Urban Mobility
Walking and transit are the backbone of sustainable mobility. Bus stops not only represent the connection between the two, but are also central in dictating the attractiveness of the latter. Accessibility of bus stops becomes, then, pivotal in increasing both attractiveness and sustainability of public transport. The paper describes a multi-step methodology to evaluate bus stops’ accessibility starting from a cluster of seven indicators describing objective and subjective features influencing passengers’ choice toward a given bus stop. The indicators are weighed by a questionnaire submitted to experts. Finally, a multicriteria analysis is developed to obtain a final score describing univocally the accessibility of each stop. Outcomes are mapped and a case study in Rome is reported as an example, with 231 bus and tram stops assessed accordingly. Results shows the relevance of the urban network and environment in evaluating the accessibility and in promoting more sustainable mobility patterns. Research innovation relies on the possibility to merge data from different fields into a specific GIS map and easily highlight for each bus stop the relationships between built environment, passengers’ comfort, and accessibility, with the concluding goal to provide advanced knowledge for further application
Safety ranking definition for infrastructures with high PTW flow
Powered two-wheelers (PTWs) provide a suitable mode for a large portion of population in many cities due to rider's personal convenience and the vehicle supposed easiness of manoeuvring. At the same time PTWs present serious safety issues compared to other motorized vehicles. This paper reports the main outcome of study carried out in Rome, where this mode is very popular and assesses the economic efforts to make infrastructure safer for PTWs. The methodology, extensively described in the paper, includes three steps: the accident analysis, the development of economic indicators of accidents costs, the maintenance priority. In the first step the location of the PTWs local accidents are identified, then the accidents are analyzed by means of the suitable indicators and, among these the safety potential (SAPO). Lastly, according to the results of the analyzed indicators the need of infrastructure maintenance will be defined. Usually SAPO is applied to rural areas, but here it has been adapted to describe the phenomena of the urban area in hand. As a result, the estimation of the saving potential to improve the infrastructure safety levels, thus reducing the amount of accidents, is presented, along with recommendations on how to upscale the SAPO at city level
A New Model for Inclusive Sports? An Evaluation of Participants’ Experiences of Mixed Ability Rugby
Sport has been recognised as a potential catalyst for social inclusion. The Mixed Ability Model represents an innovative approach to inclusive sport by encouraging disabled and non-disabled players to interact in a mainstream club environment. However, research around the impacts of the Model is currently lacking. This paper aims to contribute empirical data to this gap by evaluating participants’ experiences of Mixed Ability Rugby and highlighting implications for future initiatives. Primary qualitative data were collected within two Mixed Ability Rugby teams in the UK and Italy through online questionnaires and focus groups. Data were analysed using Simplican et al.’s (2015) model of social inclusion. Data show that Mixed Ability Rugby has significant potential for achieving inclusionary outcomes. Positive social impacts, reported by all participants, regardless of (dis)ability, include enhanced social networks, an increase in social capital, personal development and fundamental perception shifts. Factors relevant to the Mixed Ability Model are identified that enhance these impacts and inclusionary outcomes. The mainstream setting was reportedly the most important, with further aspects including a supportive club environment and promotion of self-advocacy. A ‘Wheel of Inclusion’ is developed that provides a useful basis for evaluating current inclusive sport initiatives and for designing new ones
Financial trading systems: Is recurrent reinforcement learning the via?
In this paper we propose a financial trading system whose trading strategy is developed by means of an artificial neural network approach based on a learning algorithm of recurrent reinforcement type. In general terms, this kind of approach consists: first, in directly specifying a trading policy based on some predetermined investor’s measure of profitability; second, in directly setting the financial trading system while using it. In particular, with respect to the prominent literature, in this contribution: first, we take into account as measure of profitability the reciprocal of the returns weighted direction symmetry index instead of the wide-spread Sharpe ratio; second, we obtain the differential version of the measure of profitability we consider, and obtain all the related learning relationships; third, we propose a simple procedure for the management of drawdown-like phenomena; finally, we apply our financial trading approach to some of the most prominent assets of the Italian stock market
Nonlinear bivariate comovements of asset prices: Theory and tests
Comovements among asset prices have received a lot of attention for several reasons. For example, comovements are important in cross-hedging and cross-speculation; they determine capital allocation both domestically and in international mean–variance portfolios and also, they are useful in investigating the extent of integration among financial markets. In this paper we propose a new methodology for the non–linear modelling of bivariate comovements. Our approach extends the ones presented in the recent literature. In fact, our methodology outlined in three steps, allows the evaluation and the statistical testing of non-linearly driven comovements between two given random variables. Moreover, when such a bivariate dependence relationship is detected, our approach solves for a polynomial approximation. We illustrate our three–steps methodology to the time series of energy related asset prices. Finally, we exploit this dependence relationship and its polynomial approximation to obtain analytical approximations of the Greeks for the European call and put options in terms of an asset whose price comoves with the price of the underlying asset
Turin, Rome and Genoa: comparison of the level of maturity of three large Italian cities towards Mobility as a Service
Mobility as a Service (MaaS) is the new urban mobility paradigm which, through a digital platform, makes all types of public and private transport services available to users. This contributes to increasing sustainability in cities and the quality of citizens' mobility. However, several factors influence the success of MaaS implementation: openness and data sharing of transport operators; citizens' familiarity and willingness to pay; policy, regulation and legislation; transport services, and infrastructures. Many of these factors are strictly related to the features of the city where MaaS has to operate, and more specifically to its maturity (including multimodality, integration, flexibility, and user-oriented approach). To this end, target users and their willingness to pay for MaaS operations require a specific assessment. This paper compares three large Italian cities - Turin, Rome and Genoa, very different in terms of size, complexity, local transport policies and potential for MaaS application-, with the final goal of outlining common and specific drivers, barriers and requirements for the successful adoption of MaaS. The research findings can provide useful insights to urban mobility decision-makers to avoid the unsuccessful implementation of MaaS, especially when dealing with cities with conservative mobility policies, such as Rome, or where MaaS is a novelty
A multiple criteria approach to map ecological-inclusive business models for sustainable development
The paper presents the first attempt to apply a multiple criteria approach to map ecological-inclusive business models and to structure their main features, in terms of sustainable development. Ecological-inclusive business models are presented in this study, and 15 cases pertaining to agro-food organisations located in Sub-Saharan Africa are considered. These companies simultaneously deliver positive social and environmental value, and confirm a well-established market presence. As far as social value is concerned, the companies included in the sample use a Bottom-of-Pyramid approach, involving low-income customers and/or low-income business partners. As for environmental value, all the analysed companies implement frugal innovation or sustainable exploitation of natural resources in the afro-food sector. One of the results that has been achieved is that of disentangling the complexity behind a triple bottom-line business model through a multidimensional analysis framework that identifies the aspects that play a fundamental role in ecological-inclusive business models. An evaluation model and the application of a multiple criteria outranking method are proposed as examples of how some criteria, such as the extent of socio-environmental concerns, strategy orientation and value of partnerships can be used to compare, rank and/or select business models to facilitate decision makers. This work presents the results of an interdisciplinary study on the social entrepreneurship field of knowledge
Use of the breeding technique to estimate the structure of the analysis 'errors of the day'
A 3D-variational data assimilation scheme for a quasi-geostrophic channel model (Morss, 1998) is used to study the structure of the background error and its relationship to the corresponding bred vectors. The "true" evolution of the model atmosphere is defined by an integration of the model and "rawinsonde observations" are simulated by randomly perturbing the true state at fixed locations. Case studies using different observational densities are considered to compare the evolution of the Bred Vectors to the spatial structure of the background error. In addition, the bred vector dimension (BV-dimension), defined by Patil et al. (2001) is applied to the bred vectors. It is found that after 3-5 days the bred vectors develop well organized structures which are very similar for the two different norms (enstrophy and streamfunction) considered in this paper. When 10 surrogate bred vectors (corresponding to different days from that of the background error) are used to describe the local patterns of the background error, the explained variance is quite high, about 85-88%, indicating that the statistical average properties of the bred vectors represent well those of the background error. However, a subspace of 10 bred vectors corresponding to the time of the background error increased the percentage of explained variance to 96-98%, with the largest percentage when the background errors are large. These results suggest that a statistical basis of bred vectors collected over time can be used to create an effective constant background error covariance for data assimilation with 3D-Var. Including the "errors of the day" through the use of bred vectors corresponding to the background forecast time can bring an additional significant improvement
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