Towards a behavioural approach to city centre parking

With the rapid development of China's economy and the further expansion of the city's size, people's living conditions have improved, and their spending power has continued to increase. The city's transportation demand has also continued to increase, bringing about the problem of people's parking difficulties. The most direct way to solve the problem of urban parking is to increase the number of parking spaces by constructing a parking lot. This method is difficult to implement due to funding problems or urban space constraints. This article takes the driver 's parking behavior influencing factors as the basis for research, Based on the study of the drivers' influencing factors, this paper analyzes the parking factors and analyzes the parking characteristics by observing the parking lot of Suning Plaza in Wuhu City, analyzing the factors affecting the parking behavior, optimizing the utilization efficiency of existing parking lots, and parking schemes. And management methods to promote the improvement of urban parking difficulties <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</sup> .

A machine learning and simulation-based dynamic parking choice model for airports

Urban complexes on top of subways as a function of intensive building groups, including residential, office, business, and other types nature of land use where parking time differences are obvious, can implement shared parking spaces, thereby reducing the index of parking allotment. Currently, the parking space allocation index for complexes is only a simple superposition of different land uses, resulting in an over-allocation of parking allotments, leading to a waste of land resources and a low utilization rate of parking allotments. Considering the factor of shared parking spaces, this paper conducted an in-depth analysis of the parking adaptability of urban complexes on top of subways and selected five urban complexes on top of subway stations in Wuhan to conduct a parking survey to analyze the parking demand characteristics. This study also investigated the parking behavior of parkers and analyzed the characteristics of parking behavior in urban complexes on top of subways as well as the current parking demand prediction methods and models, establishing a parking demand prediction model based on shared parking spaces and conducting an adaptability analysis. Finally, using five urban complexes in Wuhan as examples, the number of parking spaces demanded by urban complexes on top of subways in 2025 was predicted, and Wuhan Golden Harvest Fashion Plaza was used as an example to verify the feasibility and implementation ability of the theoretical and applied research in this paper.

Internet of Things has changed the environment dramatically, it introduced the all-time connectivity at the level of individual user and enabled monitoring of all user activities by connecting various sensors and data sources into the IoT ecosystem. This was supported by publish/subscribe infrastructure that efficiently interconnects all data flows. In such, global, dynamic and heterogeneous environment satisfactory performance of the underling layer for information exchange is crucial in order to support IoT services in production deployment. Therefore, to plan and support all services it is necessary to investigate the performance of the publish/subscribe middleware in details, as opposed to the overall performance analysis where the publish/subscribe middleware is analyzed as black-box. Detailed analysis provides insights in the performance of the whole system, identifies possible bottlenecks and provides information about maximum throughputs that can be handled with given parameters. In this paper we extended the CUPUS middleware with the performance monitoring components that allowed detailed insight into processing time at internal components. This allowed us to model processing times at individual component with well-know distribution (such as exponential). Such data can be used to perform complex analysis of performance of the whole middleware.

Highways that cross natural reserves are an intrusion with a nonnegligible negative impact on the behavior of wild animals and have numerous and diverse ecological impacts on wildlife near road areas. Field experiments were carried out to collect traffic flow data on the Qinghai‐Tibet Highway on the Qinghai‐Tibet Plateau, China, and the behavior of the Tibetan antelope crossing the highway was observed. The relationships between the percentage of antelopes successfully crossing the highway and the different traffic flows were analyzed. The results demonstrate that the traffic volume is the main factor affecting the success rate of Tibetan antelopes when crossing the highway, displaying a nonlinear negative correlation. Furthermore, the behavioral responses of the Tibetan antelopes within 500 m of the Qinghai‐Tibet Highway before and after different parking behaviors were observed and the proportions of the different behaviors exhibited by the Tibetan antelopes affected by different driver parking behaviors were analyzed. Parking behaviors were found to have the most significant effect on Tibetan antelope behavior within 400 m of the highway, where parking with somebody getting out having the most prominent impact. The results of this study can guide engineering measures to protect wildlife in the plateau region.

With the development of the city, the parking trouble is becoming an outstanding social and transport problem. A reasonable parking pricing scheme makes contribution to improve the use efficiency of parking and to reduce traffic congestion. The paper employs the theories and methods of behavior science to analyze parking behavior spatial structure, and establish the parking pricing model based on parking choice behavior. An algorithm based on the method of restricted capacity and incremental assignment was designed. Parking plays an important role in the traffic system of most major cities. With the developing city, the parking trouble is becoming an outstanding social and transport problem, such as motorists have been observed spending a significant percentage of their total trip time searching for a car park space. Within the city, this can deteriorate the status of traffic congestion and environmental quality. At the same time, unreasonable parking pricing will cause an unreasonable usage of the parking lot. Hence, the parking pricing model based on parking choice behavior is being a noteworthy problem in the traffic field. For solved parking problem in city, there are three stages in the developed country (GUAN, 2002). First is increase capacity of car parking lots, so that increase supply of parking for parking demand. Second is control capacity of parking lots in urban center, and control traffic demand. Three is make use of parking policy to adjust traffic structure of the city. In China, the most of city are actively planning and building parking lots to increase parking supply. But this method of resolved parking problem is unfeasible because there are many conditionality ingredients, such as land, capital, and so on. So it is a necessary choice that using policy and control means to achieve basic spatial-temporal equilibrium between supply and demand in the traffic system. For coming true this goal, it is one of possible approaches that made a reasonable parking fee to regulate the demand of parking. Many studiers already brought forward many parking pricing models, but these models cannot reflect the relationship between the parking fee and the parking choice behavior. This paper describes a parking pricing model based on parking behavior, and an algorithm of this model is designed.

In online communities, polarization refers to the phenomenon in which individuals become more divided and extreme in their opinions due to their exposure to specific content. In this paper, we present a network-based framework for evaluating polarization levels in Online Social Networks (OSNs). Starting from a dataset of comments, our framework creates a network of user interactions and leverages the Louvain algorithm, the Rao’s Quadratic Entropy, and ego networks to assess the polarization level of communities and the most influential users. To test our framework, we leveraged a dataset of tweets about climate change. After performing Extraction, Transformation and Loading activities on the dataset, we evaluated its labels, identified communities, and analyzed their polarization level and that of the most influential users. We also analyzed the ego networks of believers and deniers and the aggressiveness of the corresponding tweets. Our analysis revealed the existence of polarized communities and homophily among the most influential users. It also showed that the type of communication used to disseminate information influences the polarization level of both communities and individual users. These results demonstrate our framework’s ability to support the polarization analysis in OSNs.

We present in this paper a novel distributed solution to a security-aware job scheduling problem in cloud computing infrastructures. We assume that the assignment of the available resources is governed exclusively by the specialized brokers assigned to individual users submitting their jobs to the system. The goal of this scheme is allocating a limited quantity of resources to a specific number of jobs minimizing their execution failure probability and total completion time. Our approach is based on the Pareto dominance relationship and implemented at an individual user level. To select the best scheduling strategies from the resulting Pareto frontiers and construct a global scheduling solution, we developed a decision-making mechanism based on the game-theoretic model of Spatial Prisoner’s Dilemma, realized by selfish agents operating in the two-dimensional cellular automata space. Their behavior is conditioned by the objectives of the various entities involved in the scheduling process and driven towards a Nash equilibrium solution by the employed social welfare criteria. The performance of the scheduler applied is verified by a number of numerical experiments. The related results show the effectiveness and scalability of the scheme in the presence of a large number of jobs and resources involved in the scheduling process.

Distributed network behaviour is increasingly attracting huge attention both in academics and industrial initiatives, and most recently machine learning has been used in every possible field, leveraging its advantages.Typically, a distributed networking allows for the execution of distributed applications which results in complex behaviours among connected systems. This complexity in itself can create grey areas and vulnerabilities in the securities of these networks, therefore predicting the behaviour of these systems both at the macro and micro level has become essential. In the past most researchers have predicted network behaviour and network attack patterns by using aggregated data, but in this paper we focus on the application of machine learning at the individual user level such that the prediction of the individual network user behaviour pattern at the micro level becomes a substasive tool in creating a realistic agent based simulation of the whole distributed network, which in turn can serve as a test bed for predicting what-if scenarios such as network attacks on the target system or exposing vulnerabilities within the target system. The simulation result was validated by comparing the simulated interaction within the simulated network to the data logged in the server logs within the real life network system. This produced a correlation above 0.8, indicating a realistic model.

&lt;p&gt;Comparison of key variables between responders and non responders&lt;/p&gt;

&lt;p&gt;Survey participant characteristics by rurality (rural vs. urban) and educational attainment (high school or less vs. more than high school). 1,717 NH and VT residents were surveyed by phone in February–March 2022&lt;/p&gt;

Introduction: In this conceptual paper, we reflect on the emergence of citizens as active participants to care integration within Western, highly professionalized care systems. We explore how this development challenges established ways of conceptualizing and practicing integrated care. Ranging from professionals’ alignment with lay caregivers to citizens taking up formal ownership of services, citizen participation is often presented as a new frontier for care integration. Still, scholarly insight into the organizational implication of integration with and by citizens (instead of ‘merely’ for citizens) remains limited. Theory/Methods: First, we select and review key publications in the field of integrated care, analyzing how citizens and communities are positioned within the process of integration. Second, we draw on literature on citizen involvement to analyze the tension between the logics by which professional services are organized and the rationale(s) for involving citizens. We draw on our own empirical studies and examples from the literature to illustrate the areas in which such tensions surface. Findings: First, we discuss three reasons why citizens’ role in integrating services deserves more attention within the field of integrated care. These include (1) citizens’ life-world perspective, enabling them to contribute to the normative frameworks that guide service integration by prioritizing which issues ‘matter’ at the local level or for particular user groups; (2) citizens’ ability to identify whether the efforts of multiple organizations and professionals give rise to barriers to service access and quality at the individual user level; and (3) citizens’ prominent role as ‘lay’ providers of care, who are at risk of being ignored or marginalized when integration is approached as a predominantly professional or managerial endeavor. Second, we explore how these three incentives for involving citizens can be at odds with professional or managerial principles that often dominate how services are organized and integrated. We discuss five key areas of competing principles or perspectives—each potentially legitimate when considered in isolation—that become increasingly salient and require careful consideration when citizens assume a more prominent role in processes of integration: Competing ‘democratic’ and ‘instrumental’ rationales for involvement Competing claims of who represents ‘the community’ Different ways of valuing and utilizing professional knowledge and lay knowledge Trying to be ‘in control’ of work processes while flexibly aligning these with and to citizens Disparate perspectives on professional care organizations’ raison d’etre Discussion/Conclusion/Lessons Learned: We discuss how these five areas of tension force us to reconsider established assumptions that often guide efforts at care integration. While highlighting the potential value of citizen involvement, we also debunk the myth of citizens as the panacea for all challenges to service integration; particularly remaining critical of opportunistic, tokenistic or instrumental attempts at fostering their involvement. Limitations/Future Research: Our paper outlines a broad agenda to recalibrate the position of citizens and communities in integrated care. Future research needs to elaborate each of these five areas in more depth, developing our insights as well as practical tools for supporting constructive citizen involvement.

PurposeThe proliferation of online brand communities has shifted control over brands from firms to consumers. Demonstrating how marketers can stimulate consumers to use these opportunities and engage with the brand in such communities, the purpose of this paper is to address the effectiveness of normative and utilitarian appeals commonly employed in practice for enhancing engagement intensity and brand equity in turn.Design/methodology/approachThis paper presents two studies at an individual user level. The first study builds on matched data on marketing actions, user behavior, and user perceptions from a Facebook brand community. The second study uses an experiment with members of a firm-hosted online brand community. The authors employ seemingly unrelated regressions while controlling for self-selection.FindingsMarketer-generated appeals have a positive effect on brand equity that is mediated by engagement intensity. However, the strength of these effects depends highly on community, user, and relationship characteristics.Practical implicationsGenerally speaking, marketer-generated appeals are effective tools for marketers to build brand equity through enhanced user engagement. However, their effectiveness can be improved when managers use a targeted approach. To offer precise managerial guidance, this paper shows how entertainment value, content consumption asymmetry (e.g. whether a user prefers user-generated content over marketer-generated content), and membership duration increase or lower the impact of appeals in building the brand through engagement intensity.Originality/valueThe authors provide evidence that appeals designed to drive user engagement in online brand communities are effective tools for boosting brand equity.

Photon counting (PhC) is an effective detection technology for underwater optical wireless communication (OWC) systems. The presence of signal-dependent Poisson shot noise and asynchronous multi-user interference (MUI) complicates the processing of received data signals, hindering the effective signal detection of PhC OWC systems. This paper proposes a novel iterative signal detection method in grant-free, multi-user, underwater PhC OWC systems with signal-dependent Poisson shot noise. We first introduce a new synchronization algorithm with a unique frame structure design. The algorithm performs active user identification and transmission delay estimation. Specifically, the estimation is performed first on a user group basis and then at the individual user level with reduced complexity and latency.We also develop a nonlinear iterative multi-user detection (MUD) algorithm that utilizes a detection window for each user to identify interfering symbols and estimate MUI on a slot-by-slot basis, followed by maximum <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a-posteriori</i> probability detection of user signals. Simulations demonstrate that our scheme achieves bit error rates comparable to scenarios with transmission delays known and signal detection perfectly synchronized.

Economic burden of diverticular disease: An observational analysis based on real world data from an Italian region