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Journal articles on the topic 'Bike and shop'
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1
Davies, E. "A lesson from a bike shop." BMJ 344, may16 1 (May 16, 2012): e3006-e3006. http://dx.doi.org/10.1136/bmj.e3006.
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Cahyadi, Albert, and Friska Natalia. "Analisis dan Perancangan Halaman Website Simulasi Perakitan Sepeda." Jurnal ULTIMA InfoSys 6, no. 2 (August 1, 2016): 102–10. http://dx.doi.org/10.31937/si.v6i2.226.
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Recently, Bike shop only sells bicycle in full bike or you can build it with components that suit you at the shop. However, these days many customer needs e-commerce web so that potential customers or buyers can shop online for their custom build bike. But if they want to see how it built, they have to see it on the shop or see other builds. The main idea of this study is to make a custom build simulation for bicycle web application for bike shop so that potential buyers could do a simulation first before they buy a custom build bike so that they know what components that suits them and know the weight, price and etc.
The objective of this study is to make the potential buyer easier to find a bike that suits their needs. The methodology of system design in this study is using Rapid Application Development Method because the method could made the process very fast and always interact with the bike shop owner so that the application right on track. The website application was built by using MySQL Database and PHP programming language. The website is divided into 2 parts, which are one for customer and one for admin for maintaining the app. In this study use Spinwarrior bike shop for the example of the website implementation
Index Terms: Bicycle, custom build, simulation, PHP, website.
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Troncoso, Leandro Dri Manfiolete, Sergio Alejandro Toro-Arevalo, and Rodolfo Franco Puttini. "A perspectiva do ciclismo urbano como sentido político em São Paulo, Brasil: experiências laborais na promoção da bicicultura." Retos, no. 36 (January 31, 2019): 129–37. http://dx.doi.org/10.47197/retos.v36i36.67355.
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O objetivo do estudo foi compreender o fenômeno ciclismo urbano como sentido político em perspectiva de experiências laborais na promoção da bicicultura em São Paulo, Brasil. Optamos pela abordagem fenomenológico-hermenêutica a partir dos geradores de sentido vínculo, abrigo, fixação, reiteração e apoio na análise dos discursos de cinco sujeitos que trabalham com mecânica de bicicleta, gerente de agência “bike courier”, organizador de eventos desportivos com mountain bike, administrador de empresa bike shop e gestora pública de infraestrutura cicloviária. Na construção dos resultados, emergiram as unidades de significado: a) valores sociais na atividade profissional com bicicleta b) saúde ambiental no compartilhamento viário c) educação e política pública para a sustentabilidade. Constatamos que, a categoria “ciclismo urbano como construção cultural” representa o sentido semântico, existencial e metafísico da manifestação política da bicicultura em direção a cidadania ativa pelo direito humano à mobilidade por bicicleta em São Paulo.
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Arnold, Lynnette. "Reproducing Actions, Reproducing Power: Local Ideologies and Everyday Practices of Participation at a California Community Bike Shop." Journal of Linguistic Anthropology 22, no. 3 (December 2012): 137–58. http://dx.doi.org/10.1111/j.1548-1395.2012.01153.x.
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Tai, Ching Hui, and Chun Ho Yin. "The Automatic Calculation of Cumulative Lamination and Analysis of the Structural Static Rigidity of Bike Frame Made of Carbon Fiber Composite." Applied Mechanics and Materials 563 (May 2014): 13–20. http://dx.doi.org/10.4028/www.scientific.net/amm.563.13.
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This paper discusses the process of calculating the lay-up configuration and structural stiffness of carbon fiber composite bike frame. First, a program is written in ANSYS macro language to calculate the lay-up configuration of the composite. The user only has to input the geometry, fiber orientation and sequence of individual layer, according to the original shop drawing. The program will then calculate the lay-up configuration of all the details for the whole structure automatically, and create the finite element model for ANSYS. The stiffness is then analyzed according to the product specification, and also compared with test result to evaluate the validation of the model. This automated process can accelerate the development time frame, and also work as the basis of parametric model for future design optimization.
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Ling, Jan. "Is ‘world music’ the ‘classic music’ of our time?" Popular Music 22, no. 2 (May 2003): 235–40. http://dx.doi.org/10.1017/s0261143003003143.
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On the way to my library there is a little shop named ‘World Music. The Oasis of Music from Asia, Africa’. One morning I stopped my bike and went in just curious to see what world music could be in my little town. In the racks even the smallest country from Asia or Africa was represented with one or two CDs, most of them produced in Paris or London. The other customers were half my age (around thirty to thirty-five, nobody over fifty or under twenty). The owner, an immigrant who has lived in Sweden for more than ten years, had this to say:The youngsters do not come here, all my customers are between twenty-five and forty. There is a growing interest in world music: people with money are visiting foreign countries as tourists and when they come home they come to me, asking for artists or groups they have heard. Most of them have an academic background and speak English fluently.
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Hu, Yang, Anae Sobhani, and Dick Ettema. "To e-bike or not to e-bike? A study of the impact of the built environment on commute mode choice in small Chinese city." Journal of Transport and Land Use 14, no. 1 (April 14, 2021): 479–97. http://dx.doi.org/10.5198/jtlu.2021.1807.
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The use of electric bikes (e-bikes) is attracting increasing attention from researchers and policymakers as a way to promote sustainable transportation. However, knowledge about the built environment factors that influence e-bike use is lacking. In China, most evidence on e-bikes and travel behavior stems from big cities; there is much less evidence concerning small cities and their adjacent rural areas. Using travel data collected in a small Chinese city (Ganyu), the present research explores the impact of the built environment around residential and work locations on individuals’ commute mode choice, with a particular focus on e-bike use. Consistent with the few previous studies on travel behavior in small Chinese cities, we find that most residents of Ganyu commute only short distances and that the e-bike is the primary mode for their daily commutes. The results of a nested logit model show that e-bike use is more popular among females and low-income groups, and that certain built environment characteristics at the work location promote e-bike use. Moreover, the built environment in different geographical contexts has different influences on commute mode choice. In particular, the presence of city/town roads without bike lanes at work locations promotes e-bike use among rural residents but much less so among urban residents.
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You, Peng-Sheng, Pei-Ju Lee, and Yi-Chih Hsieh. "An artificial intelligent approach to the bicycle repositioning problems." Engineering Computations 34, no. 1 (March 6, 2017): 145–63. http://dx.doi.org/10.1108/ec-11-2015-0334.
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Purpose Many bike rental organizations permit customers to pick-up bikes from one bike station and return them at a different one. However, this service may result in bike imbalance, as bikes may accumulate in stations with low demand. To overcome the imbalance problem, this paper aims to develop a decision model to minimize the total costs of unmet demand and empty bike transport by determining bike fleet size, deployments and the vehicle routing schedule for bike transports. Design/methodology/approach This paper developed a constrained mixed-integer programming model to deal with this bike imbalance problem. The proposed model belongs to the non-deterministic polynomial-time (NP)-hard problem. This paper developed a two-phase heuristic approach to solve the model. In Phase 1, the approach determines fleet size, deployment level and the number of satisfied demands. In Phase 2, the approach determines the routing schedule for bike transfers. Findings Computational results show the following results that the proposed approach performs better than General Algebraic Modeling System (GAMS) in terms of solution quality, regardless of problem size. The objective values and the fleet size of rental bikes allocated increase as the number of rental stations increases. The cost of transportation is not directly proportional to the number of bike stations. Originality/value The authors provide an integrated model to simultaneously deal with the problems of fleet sizing, empty-resource repositioning and vehicle routing for bike transfer in multiple-station systems, and they also present an algorithm that can be applied to large-scale problems which cannot be solved by the well-known commercial software, GAMS/CPLEX.
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Bertero, Christophe, Jean-François Léon, Gilles Trédan, Mathieu Roy, and Alexandre Armengaud. "Urban-Scale NO2 Prediction with Sensors Aboard Bicycles: A Comparison of Statistical Methods Using Synthetic Observations." Atmosphere 11, no. 9 (September 22, 2020): 1014. http://dx.doi.org/10.3390/atmos11091014.
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Mobile devices for city-scale air quality monitoring is receiving increasing attention due to the advent of low-cost and miniaturized sensors. Mobility and crowdsensing have emerged as a new means to investigate the ambient air quality in urban areas. However, the design of the network (e.g., number of sensors per unit area) and the scientific interpretation of collected data with an ad hoc method are still challenging. In this paper, we focus on the use of a fleet of private bicycles to monitor NO2 concentrations in the city of Marseille, France. The study is based on synthetic observations generated by means of a regional air quality simulation system at a spatial resolution of 25 m × 25 m and simulated bike trips that are randomly generated in the city. The bike trips correspond to a maximum of 4500 bike commuters and are generated using a web-based navigation service. Simulated bike tracks are validated using available statistics on bike counts. Each bike track is associated with the along-track corresponding NO2 concentrations collected from the air quality simulations and physical features on the ground collected from Open Street Map. Spatialization of the information collected aboard the bikes is tested by using three different algorithms: kriging, land-use regression (LUR) and neural network (NN). LUR and NN show that the fleet can be limited to below 100 bikes while the performance of kriging is steadily increasing with the number of bikes. Increasing the sample distance above 200 m also impairs the citywide prediction of simulated NO2 concentrations.
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Bieliński, Tomasz, and Agnieszka Ważna. "Hybridizing bike-sharing systems: the way to improve mobility in smart cities." Transport Economics and Logistics 79 (October 23, 2018): 53–63. http://dx.doi.org/10.26881/etil.2018.79.04.
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New generation of bike-sharing systems introduce a wide range of smart solutions. Dockless bicycles equipped with GPS and accessible by smartphone applications as well as electric bikes are considered to be solutions to many socioeconomic and environmental urban problems. However, older generation of bike-sharing systems equipped with dockings stations have some advantages over free floating public bicycles. The aim of this paper is to examine if hybridization of both systems may become an opportunity to improve bike-sharing services. The paper presents characteristics of both types of bike-sharing schemes and describes the examples of hybrid models to show benefits of this solution. Chosen methodology is the case study of selected European bike-sharing systems which combine features of both schemes – the dockless and the station-based.
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Spörri, Emilian, Sascha Halvachizadeh, Jamison G. Gamble, Till Berk, Florin Allemann, Hans-Christoph Pape, and Thomas Rauer. "Comparison of Injury Patterns between Electric Bicycle, Bicycle and Motorcycle Accidents." Journal of Clinical Medicine 10, no. 15 (July 29, 2021): 3359. http://dx.doi.org/10.3390/jcm10153359.
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Background: Electric bicycles (E-bikes) are an increasingly popular means of transport, and have been designed for a higher speed comparable to that of small motorcycles. Accident statistics show that E-bikes are increasingly involved in traffic accidents. To test the hypothesis of whether accidents involving E-bikes bear more resemblance to motorcycle accidents than conventional bicyclists, this study evaluates the injury pattern and severity of E-bike injuries in direct comparison to injuries involving motorcycle and bicycle accidents. Methods: In this retrospective cohort study, the data of 1796 patients who were treated at a Level I Trauma Center between 2009 and 2018 due to traffic accident, involving bicycles, E-bikes or motorcycles, were evaluated and compared with regard to injury patterns and injury severity. Accident victims treated as inpatients at least 16 years of age or older were included in this study. Pillion passengers and outpatients were excluded. Results: The following distribution was found in the individual groups: 67 E-bike, 1141 bicycle and 588 motorcycle accidents. The injury pattern of E-bikers resembled that of bicyclists much more than that of motorcyclists. The patients with E-bike accidents were almost 14 years older and had a higher incidence of moderate traumatic brain injuries than patients with bicycle accidents, in spite of the fact that E-bike riders were nearly twice as likely to wear a helmet as compared to bicycle riders. The rate of pelvic injuries in E-bike accidents was twice as high compared with bicycle accidents, whereas the rate of upper extremity injuries was higher following bicycle accidents. Conclusion: The overall E-bike injury pattern is similar to that of cyclists. The differences in the injury pattern to motorcycle accidents could be due to the higher speeds at the time of the accident, the different protection and vehicle architecture. What is striking, however, is the higher age and the increased craniocerebral trauma of the E-bikers involved in accidents compared to the cyclists. We speculate that older and untrained people who have a slower reaction time and less control over the E-bike could benefit from head protection or practical courses similar to motorcyclists.
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Zhou, Yajun, Lilei Wang, Rong Zhong, and Yulong Tan. "A Markov Chain Based Demand Prediction Model for Stations in Bike Sharing Systems." Mathematical Problems in Engineering 2018 (2018): 1–8. http://dx.doi.org/10.1155/2018/8028714.
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Accurate transfer demand prediction at bike stations is the key to develop balancing solutions to address the overutilization or underutilization problem often occurring in bike sharing system. At the same time, station transfer demand prediction is helpful to bike station layout and optimization of the number of public bikes within the station. Traditional traffic demand prediction methods, such as gravity model, cannot be easily adapted to the problem of forecasting bike station transfer demand due to the difficulty in defining impedance and distinct characteristics of bike stations (Xu et al. 2013). Therefore, this paper proposes a prediction method based on Markov chain model. The proposed model is evaluated based on field data collected from Zhongshan City bike sharing system. The daily production and attraction of stations are forecasted. The experimental results show that the model of this paper performs higher forecasting accuracy and better generalization ability.
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He, Liu, Tangyi Guo, and Kun Tang. "Dynamic Scheduling Model of Bike-Sharing considering Invalid Demand." Journal of Advanced Transportation 2020 (December 15, 2020): 1–10. http://dx.doi.org/10.1155/2020/8843783.
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System resources allocation optimization through dynamic scheduling is key to improving the service level of bike-sharing. This study innovatively introduces three types of invalid demand with negative effect including waiting, transfer, and abandoning, which consists of the total demand of bike-sharing system. Through exploring the dynamic relationship among users’ travel demands, the quantity and capacity of bikes at the rental points, the records of bicycles borrowed and returned, and the vehicle scheduling schemes, a demand forecasting model for bike-sharing is established. According to the predicted bikes and the maximum capacity limit at each rental point, an optimization model of scheduling scheme is proposed to reduce the invalid demand and the total scheduling time. A two-layer dynamic coupling model with iterative feedback is obtained by combining the demand prediction model and scheduling optimization model and is then solved by Nicked Pareto Genetic Algorithm (NPGA). The proposed model is applied to a case study and the optimal solution set and corresponding Pareto front are obtained. The invalid demand is greatly reduced from 1094 to 26 by an effective scheduling of 3 rounds and 96 minutes. Empirical results show that the proposed model is able to optimize the resource allocation of bike-sharing, significantly reduce the invalid demand caused by the absence of bikes at the rental point such as waiting in a place, walking to other rental points, and giving up for other travel modes, and effectively improve the system service level.
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Bui, Van-Tung, Chyi-Ren Dow, Yu-Chi Huang, Pei Liu, and Vu Duc Thai. "A Canopen-Based Gateway and Energy Monitoring System for Electric Bicycles." Energies 13, no. 15 (July 22, 2020): 3766. http://dx.doi.org/10.3390/en13153766.
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The limitation of battery capacity is a cause of range anxiety that reduces the wide use of electric bicycles (e-bikes). Therefore, many works have developed systems that provide assistance to cyclists to deal with the range anxiety problem. However, these systems may have limited applications since they can only work with the e-bike manufacturers’ hardware and communication protocols. This paper proposes an energy monitoring system (EMS) for e-bikes, which is based on EnergyBus, a standardized hardware and communication protocol for e-bikes. EnergyBus standard is based on controller area network (CAN) bus and CANopen protocols. EMS comprises a gateway connected to EnergyBus of e-bike and an EMS application installed on a smart device that connects to the gateway via Bluetooth. The gateway provides CAN bus monitoring and CANopen device data access services to the smart device. These services are modeled to determine gateway parameters to ensure the efficient performance of the gateway and to keep the working status of the monitored e-bike safe. The EMS application provides the cyclist information about battery status, rider efforts, and other related information such as distance and speed. Experimental results show that the proposed gateway can monitor data in real-time and ensure monitored system safety.
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Usama, Muhammad, Yongjun Shen, and Onaira Zahoor. "Towards an Energy Efficient Solution for Bike-Sharing Rebalancing Problems: A Battery Electric Vehicle Scenario." Energies 12, no. 13 (June 28, 2019): 2503. http://dx.doi.org/10.3390/en12132503.
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A free-float bike-sharing system faces various operational challenges to maintain good service quality while optimizing the operational cost. The primary problems include the fulfillment of the users demand at all stations, and the replacement of faulty bikes presented in the system. This study focuses on a free-float bike-sharing system rebalancing problem (FFBP) with faulty bikes using battery electric vehicles (BEVs). The target inventory of bikes at each station is obtained while minimizing the total traveling time through the presented formulation. Using CPLEX solver, the model is demonstrated through numerical experiments considering the various vehicle and battery capacities, and a cost–benefit analysis is performed for BEV and conventional internal combustion engine vehicles (ICEVs) while taking the BEV manufacturing and indirect emission into account. The results show that the annual cost incurred on an ICEV is 56.9% more as compared to the cost of using an equivalent BEV. Since BEVs consume less energy than conventional ICEVs, the use of BEVs for rebalancing the bike-sharing systems results in significant energy savings for an urban transport network. Moreover, the life cycle emissions of an ICEV are 48.3% more as compared to an equivalent BEV. Furthermore, the operational cost of a BEV significantly reduces with the increase in battery capacity.
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Yao, Yao, Linwei Liu, Zibin Guo, Ziheng Liu, and Huiyu Zhou. "Experimental Study on Shared Bike Use Behavior under Bounded Rational Theory and Credit Supervision Mechanism." Sustainability 11, no. 1 (December 27, 2018): 127. http://dx.doi.org/10.3390/su11010127.
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As a new travel model, the bike-sharing system (BSS) solves the ‘last kilometer’ problem and has developed rapidly for its convenience. However, many accompanying problems have emerged. In China, parking violation problems—such as severe traffic congestion—are caused by dock-less shared bikes. Furthermore, a large number of shared bikes have to be scrapped early for vandalism. As a special form of public good, bike-sharing also faces the dilemma of negative externalities. Seeking a solution, Mobike has conducted a credit supervision mechanism, which transfers the users’ different behavior to credits for user behavior regulation, but with unsatisfactory results. The goal of the paper is to test the validity of credit supervision mechanism from user’s perspective to regulate the abuse of sharing bike by simulating the use scenario of BSS in real life in a lab experiment based on induced value theory. The behavioral and pre- and post-experiment survey data were thoroughly analyzed. The results show that, within a negative context, the credit supervision system has a more significant effect on inducing proper user behavior, which improves after adding a real-time feedback mechanism. Finally, we provide effective suggestions to policy makers and shared bike companies for inducing positive user behavior.
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Lee, Euntak, Bongsoo Son, and Youngjun Han. "Optimal Relocation Strategy for Public Bike System with Selective Pick-Up and Delivery." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 4 (March 11, 2020): 325–36. http://dx.doi.org/10.1177/0361198120912232.
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Public bike-sharing systems in many countries provide convenience as users can rent or return a bike freely at any station, but this may cause a demand–supply imbalance of the bike inventory for certain stations. To solve this issue, this research develops a bike-relocation strategy including both demand prediction and relocating route optimization. First, the bike demand is estimated by a least-square boosting algorithm, and numbers of relocating bikes are decided comparing bike inventories at each station. Second, based on predicted demand, the number of transporting vehicles and relocating routes are optimized by genetic algorithm. The strategy aims to minimize service vehicle numbers and relocating time with selective pick-up and delivery. The proposed strategy is evaluated by applying it to a real-world public bike system in Gangnam-district in Seoul, South Korea, and the results show the system can be improved significantly. Specifically, the bike demand satisfaction ratio increases from 0.87 to 1.00 in the morning peak hour, which shows that the proposed strategy better satisfies the bike demand. The uniformity of spare inventory is also improved, as a coefficient of variation decreases from 0.73 to 0.56. The reasonableness index, which reflects a sufficient number of bike stands, indicates 87% and 92% stations have a proper number of stands at morning peak hour and 24 h, respectively, with respect to predicted demand. The results show that the bike system with the proposed strategy has more reliability with stable inventory, and the operating cost could decrease with fewer relocating vehicles and optimized vehicle routes.
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Guo, Tangyi, Jie Yang, Liu He, and Kun Tang. "Emerging Technologies and Methods in Shared Mobility Systems Layout Optimization of Campus Bike-Sharing Parking Spots." Journal of Advanced Transportation 2020 (November 1, 2020): 1–10. http://dx.doi.org/10.1155/2020/8894119.
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The rapid development of bike sharing has posed some challenges to the traffic management on campus. The bike sharing on campus has problems such as messy parking, and some buildings in the peak hours have no bikes to borrow. Thus, alternative parking spots are proposed based on the layout principle of parking spots for bicycles. An optimization model of the layout of campus bike-sharing parking spots with travel time and construction cost as the optimization goal is established, and the branch and bound algorithm is used to solve the model. Finally, the study analysis is carried out by optimizing the layout of the bike-sharing parking spot of Nanjing University of Science and Technology. The results show that, after optimizing the layout of parking spots, the average travel time of users is reduced by 6.0%, and the total construction cost is reduced by 27.3%. While being convenient for campus bike-sharing users, it also provides scientific decision-making support for the campus traffic management.
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Festa, Demetrio, and Carmen Forciniti. "Attitude towards Bike Use in Rende, a Small Town in South Italy." Sustainability 11, no. 9 (May 13, 2019): 2703. http://dx.doi.org/10.3390/su11092703.
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The bike can contribute to the development of sustainable mobility. This requires interventions to promote bike use, such as increasing the cyclist safety, construction of bikeways, and provision of ancillary services and bike sharing activities. In the literature many studies focus on bike use and agree with the application of such interventions. However, these studies are often related to specific urban areas that are very different; the transferability of results and models has not been adequately analyzed. This work investigates the attitudes towards cycling in Rende, a small town in Southern Italy. The aim is to determine in what conditions the users would be willing to use bicycles in relation to the trip purpose, the presence or absence of cycle paths, and the availability of bike sharing services. Different factors, such as age, gender, and occupation, are taken into account. The results show that the bike use could be incentivized by enlarging the existent bike network, adopting bike sharing systems, and promoting specific policies oriented to sustainable transport modes. Furthermore, two aspects emerged from the analysis: the importance of studying the propensity to use bikes by different groups of users and the importance of focusing interventions on market segments with greater willingness to bike.
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Ma, Yang, Zhou, Feng, and Yuan. "Risk Riding Behaviors of Urban E-Bikes: A Literature Review." International Journal of Environmental Research and Public Health 16, no. 13 (June 28, 2019): 2308. http://dx.doi.org/10.3390/ijerph16132308.
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In order to clearly understand the risky riding behaviors of electric bicycles (e-bikes) and analyze the riding characteristics, we review the research results of the e-bike risky riding behavior from three aspects: the characteristics and causes of e-bike accidents, the characteristics of users’ traffic behavior, and the prevention and intervention of traffic accidents. The analysis results show that the existing research methods on risky riding behavior of e-bikes mainly involve questionnaire survey methods, structural equation models, and binary probability models. The illegal occupation of motor vehicle lanes, over-speed cycling, red-light running, and illegal manned and reverse cycling are the main risky riding behaviors seen with e-bikes. Due to the difference in physiological and psychological characteristics such as gender, age, audiovisual ability, responsiveness, patience when waiting for a red light, congregation, etc., there are differences in risky cycling behaviors of different users. Accident prevention measures, such as uniform registration of licenses, the implementation of quasi-drive systems, improvements of the riding environment, enhancements of safety awareness and training, are considered effective measures for preventing e-bike accidents and protecting the traffic safety of users. Finally, in view of the shortcomings of the current research, the authors point out three research directions that can be further explored in the future. The strong association rules between risky riding behavior and traffic accidents should be explored using big data analysis. The relationships between risk awareness, risky cycling, and traffic accidents should be studied using the scales of risk perception, risk attitude, and risk tolerance. In a variety of complex mixed scenes, the risk degree, coupling characteristics, interventions, and the coupling effects of various combination intervention measures of e-bike riding behaviors should be researched using coupling theory in the future.
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Wang, Sishen, Hao Wang, Pengyu Xie, and Xiaodan Chen. "Life-Cycle Assessment of Carbon Footprint of Bike-Share and Bus Systems in Campus Transit." Sustainability 13, no. 1 (December 25, 2020): 158. http://dx.doi.org/10.3390/su13010158.
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Low-carbon transport system is desired for sustainable cities. The study aims to compare carbon footprint of two transportation modes in campus transit, bus and bike-share systems, using life-cycle assessment (LCA). A case study was conducted for the four-campus (College Ave, Cook/Douglass, Busch, Livingston) transit system at Rutgers University (New Brunswick, NJ). The life-cycle of two systems were disaggregated into four stages, namely, raw material acquisition and manufacture, transportation, operation and maintenance, and end-of-life. Three uncertain factors—fossil fuel type, number of bikes provided, and bus ridership—were set as variables for sensitivity analysis. Normalization method was used in two impact categories to analyze and compare environmental impacts. The results show that the majority of CO2 emission and energy consumption comes from the raw material stage (extraction and upstream production) of the bike-share system and the operation stage of the campus bus system. The CO2 emission and energy consumption of the current campus bus system are 46 and 13 times of that of the proposed bike-share system, respectively. Three uncertain factors can influence the results: (1) biodiesel can significantly reduce CO2 emission and energy consumption of the current campus bus system; (2) the increased number of bikes increases CO2 emission of the bike-share system; (3) the increase of bus ridership may result in similar impact between two systems. Finally, an alternative hybrid transit system is proposed that uses campus buses to connect four campuses and creates a bike-share system to satisfy travel demands within each campus. The hybrid system reaches the most environmentally friendly state when 70% passenger-miles provided by campus bus and 30% by bike-share system. Further research is needed to consider the uncertainty of biking behavior and travel choice in LCA. Applicable recommendations include increasing ridership of campus buses and building a bike-share in campus to support the current campus bus system. Other strategies such as increasing parking fees and improving biking environment can also be implemented to reduce automobile usage and encourage biking behavior.
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Lv, Hongtao, Chaoli Zhang, Zhenzhe Zheng, Tie Luo, Fan Wu, and Guihai Chen. "Mechanism Design with Predicted Task Revenue for Bike Sharing Systems." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 02 (April 3, 2020): 2144–51. http://dx.doi.org/10.1609/aaai.v34i02.5589.
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Bike sharing systems have been widely deployed around the world in recent years. A core problem in such systems is to reposition the bikes so that the distribution of bike supply is reshaped to better match the dynamic bike demand. When the bike-sharing company or platform is able to predict the revenue of each reposition task based on historic data, an additional constraint is to cap the payment for each task below its predicted revenue. In this paper, we propose an incentive mechanism called TruPreTar to incentivize users to park bicycles at locations desired by the platform toward rebalancing supply and demand. TruPreTar possesses four important economic and computational properties such as truthfulness and budget feasibility. Furthermore, we prove that even when the payment budget is tight, the total revenue still exceeds or equals the budget. Otherwise, TruPreTar achieves 2-approximation as compared to the optimal (revenue-maximizing) solution, which is close to the lower bound of at least √2 that we also prove. Using an industrial dataset obtained from a large bike-sharing company, our experiments show that TruPreTar is effective in rebalancing bike supply and demand and, as a result, generates high revenue that outperforms several benchmark mechanisms.
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Nikiforiadis, Andreas, Georgia Ayfantopoulou, and Afroditi Stamelou. "Assessing the Impact of COVID-19 on Bike-Sharing Usage: The Case of Thessaloniki, Greece." Sustainability 12, no. 19 (October 5, 2020): 8215. http://dx.doi.org/10.3390/su12198215.
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The COVID-19 pandemic had a significant effect in urban mobility, while essential changes are being observed in travelers’ behavior. Travelers in many cases shifted to other transport modes, especially walking and cycling, for minimizing the risk of infection. This study attempts to investigate the impact that COVID-19 had on travelers’ perceptions towards bike-sharing systems and whether the pandemic could result in a greater or lesser share of trips that are being conducted through shared bikes. For that reason, a questionnaire survey was carried out in the city of Thessaloniki, Greece, and the responses of 223 people were analyzed statistically. The results of the analysis show that COVID-19 will not affect significantly the number of people using bike-sharing for their trips. However, for a proportion of people, bike-sharing is now more attractive. Moreover, the results indicate that bike-sharing is now more likely to become a more preferable mobility option for people who were previously commuting with private cars as passengers (not as drivers) and people who were already registered users in a bike-sharing system. The results also provide evidence about the importance of safety towards COVID-19 for engaging more users in bike-sharing, in order to provide them with a safe mobility option and contribute to the city’s resilience and sustainability.
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Suchanek, Michał, Aleksander Jagiełło, and Justyna Suchanek. "Substitutability and Complementarity of Municipal Electric Bike Sharing Systems against Other Forms of Urban Transport." Applied Sciences 11, no. 15 (July 21, 2021): 6702. http://dx.doi.org/10.3390/app11156702.
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The current quantitative and qualitative development of bike-sharing systems worldwide involves particular implications regarding the level of sustainability of urban development and city residents’ quality of life. To make these implications as large as possible as well as the most positive, it is essential that the people who use municipal bikes on a regular basis to the largest extent possible abandon car travel at the same time. Thanks to their operational characteristics, electric bikes should enable meeting the transport needs of a wider group of city residents compared with traditional bicycles. The main aim of this study was therefore to check whether the municipal electric bike system (MEVO) in Gdańsk-Gdynia-Sopot metropolitan area of Poland lived up to the hopes placed upon it by policymakers. Therefore, the article tests the hypothesis indicating that the municipal electric bike systems constitute a substitutable form of transportation against passenger cars to a larger extent than against collective urban transport and walking trips. The analysis was performed based on the results of primary studies conducted among the users of MEVO. The data show that the MEVO was a substitutable form of transportation against collective transport and walking trips to a larger extent than against passenger cars. Through logistic regression analysis, the variables concerning the probability of replacing car trips by MEVO bicycles were determined. Among the analyzed variables, the following turned out to be statistically significant: age, the number of people in the household, the number of cars in the household, the distance from work, and gender. The results therefore indicate that substituting in favor of electro bikes was more probable for younger people with fewer people in the household and a distance to travel below 3 km, whereas it was less probable for people with more cars in the household or traveling a distance longer than 10 km. Additionally, females were more likely to choose the bike system.
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Yan, Qiang, Kun Gao, Lijun Sun, and Minhua Shao. "Spatio-Temporal Usage Patterns of Dockless Bike-Sharing Service Linking to a Metro Station: A Case Study in Shanghai, China." Sustainability 12, no. 3 (January 23, 2020): 851. http://dx.doi.org/10.3390/su12030851.
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The dockless bike-sharing (DLBS) system serves as a link between metro stations and travelers’ destinations (or originations). This paper aims to uncover spatio-temporal usage patterns of dockless bike-sharing service linking to metro stations for supporting scientific planning and management of the dockless bike-sharing system. A powerful visualization tool was used to analyze the differences in usage patterns in workdays and weekends. The travel distance distributions of using dockless bike-sharing near metro stations were investigated to shed light on the service area of the dockless bike-sharing system. Agglomerative hierarchical clustering was applied to analyze differences in usage patterns of metro stations located in different areas. The results show that the usage patterns of dockless bike-sharing on weekends are different from those on workdays. The average travel distance using the dockless bike-sharing system at weekends is significantly larger than that of workdays. The travel distance distribution could be nicely fitted by the Fréchet distribution of the Generalized Extreme Value (GEV) distribution family. The usage characteristics of shared bikes are correlated with land use and population density around metro stations. No matter in urban or suburban areas, there is a great demand for bike-sharing in densely populated areas with intensive land development, such as university towns in suburban areas. This study improves the understandings regarding the usage patterns of the DLBS system serving as a link between the final destinations (or originations) and metro stations. The results can be helpful to the operation and demand management of DLBS.
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Neumann-Saavedra, Bruno Albert, Teodor Gabriel Crainic, Bernard Gendron, Dirk Christian Mattfeld, and Michael Römer. "Integrating Resource Management in Service Network Design for Bike-Sharing Systems." Transportation Science 54, no. 5 (September 2020): 1251–71. http://dx.doi.org/10.1287/trsc.2019.0950.
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Station-based bike-sharing systems rely on bike redistribution to provide users with an adequate service level. We propose a novel formulation of service network design that coordinates redistribution decisions in space and time to plan regular master tours. This formulation explicitly integrates resource-management decisions by considering a limited redistribution budget to acquire and operate vehicles, as well as an accurate time representation of pickups and deliveries of bikes at stations. We propose a matheuristic relying on a neighborhood search scheme to find solutions of good quality for real-world-sized problem instances in reasonable time. To produce starting solutions, we propose a construction heuristic decomposing the daytime redistribution process into three sequential phases: determine pickups and deliveries, link pickups and deliveries into transport requests, and assign transport requests to master tours. We evaluate the operational performance of master tours with a discrete-event simulation approach. We show that master tours improve the level of service in bike-sharing systems with high and regular mobility patterns, for example, commuting activities.
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Cotnam, Victoria, and Aleksandra Zecevic. "MEASURING THE EFFECTS OF A CYCLING PROGRAM ON QUALITY OF LIFE OF OLDER ADULTS LIVING IN LONG TERM CARE." Innovation in Aging 3, Supplement_1 (November 2019): S848—S849. http://dx.doi.org/10.1093/geroni/igz038.3123.
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Abstract Cycling Without Age (CWA) is a program offered in long-term care (LTC) homes around the world that allows older adults who are unable to ride a bicycle the pleasure of a bike ride again. Two residents sit in the front bench seat of a trishaw, and a volunteer bike pilot pedals the bike. A variety of anecdotal benefits have been reported and no study has rigorously measured the effects of this program. The purpose of this research is to measure the effects of the CWA program on happiness and quality of life of LTC home residents, through observation of an existing program in a Canadian LTC home. A total of 24 residents were purposefully recruited in a biking group (n=23) who were biked twice a week for 12 weeks, and a strolls group (n=16) who went for outdoors walks or wheelchair rides for the same period of time. Data on pain, cognition, social engagement, and aggressive behaviour was harvested from the Resident-Assessment Instrument – Minimum Data Set (RAI-MDS). Happiness was measured pre and post all bike rides and strolls using a visual analogue scale, and the LTC QoL assessment was used to assess QOL. Findings show that biking group scored higher on happiness after bike rides compared to before, as well as compared to strolls. Bike group QOL scores are higher at the end of the 12 weeks than were strolls group. In summary, CWA shows potential to increase QOL and happiness of residents living in LTC.
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Fardila, Dinda, Henricus Priyosulistyo, and Andreas Triwiyono. "PENILAIAN FASILITAS JALUR PEDESTRIAN DARI ASPEK SAFETY, HEALTH, AND ENVIRONMENT (SHE)." INERSIA: lNformasi dan Ekspose hasil Riset teknik SIpil dan Arsitektur 14, no. 2 (December 21, 2018): 133–45. http://dx.doi.org/10.21831/inersia.v14i2.22536.
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ABSTRACTPedestrian way is a space providing services for pedestrian in carrying out their activities. This research aims to evaluate the liability of the pedestrian facilities in complying the prevailing standards and safety, health, and environment (SHE) instead of determining the priority rank for improving the performance of pedestrian facilities. This research was conducted on the pedestrian way of Malioboro area in Yogyakarta, by field survey on 23-27 January 2018. The research used questionnaires with incidental sampling technique. The data was performed and statistically analyzed by SPSS program in terms of Importance Performance Analysis (IPA) method and inference analysis using Rank Spearman's truth test. The result of this research showed that the pedestrian way had generally met the standards (57.14%) but several facilities (38.10%) did not meet the criteria and 4.76% was not available in the pedestrian way of Malioboro.The level of performance of pedestrian facilities based on SHE was mostly high (satisfied). The facilities that must be improved were the cleanliness of the pedestrian way and the toilet. Some respondences were still able to accept the conditions as follow: the speed of motor bike, the noises, street vendor layout, shop sign layout and the quality of building materials. Keywords: Environment, Importance Performance Analysis (IPA), Pedestrian way, Safety, Health ABSTRAKJalur pedestrian merupakan ruang yang memberikan layanan kepada pejalan kaki dalam melakukan aktivitasnya. Kajian ini bertujuan untuk mengevaluasi kelayakan kondisi fasilitas jalur pedestrian terhadap standar yang berlaku, safety, health, and environment (SHE), dan menentukan prioritas layanan yang diperlukan untuk peningkatan kinerja fasilitas jalur pedestrian. Kajian ini dilakukan pada jalur pedestrian Kawasan Malioboro dengan cara survey lapangan pada tanggal 23-27 Januari 2018. Kajian ini menggunakan kuesioner berskala Likert dengan teknik pengambilan sampel insidental sampling.Analisis data menggunakan analisis statistik deskriptif, metode Importance Performance Analysis (IPA) dan analisis inferensi (uji korelasi Spearman Rank). Hasil kajian menunjukkan bahwa fasilitas jalur pedestrian telah memenuhi standarsebesar 57,14%, tetapi 38,10% tidak memenuhi kriteria dan 4,76% fasilitas tidak terdapat di jalur pedestrian kawasan Malioboro. Fasilitas yang harus ditingkatkan kinerjanya pada prioritas utama adalah tingkat kebersihan pedestrian dan toilet. Beberapa pedestrian masih dapat menerima kondisi berikut :kecepatan pengendara bermotor, kebisingan, tata letak PKL, tata letak papan nama toko dan kualitas bahan bangunan. Kata kunci: Environment, Importance Performance Analysis (IPA), Jalur pedestrian, Safety, Health
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Lahoorpoor, Bahman, Hamed Faroqi, Abolghasem Sadeghi-Niaraki, and Soo-Mi Choi. "Spatial Cluster-Based Model for Static Rebalancing Bike Sharing Problem." Sustainability 11, no. 11 (June 8, 2019): 3205. http://dx.doi.org/10.3390/su11113205.
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Bike sharing systems, as one of the complementary modes for public transit networks, are designed to help travelers in traversing the first/last mile of their trips. Different factors such as accessibility, availability, and fares influence these systems. The availability of bikes at certain times and locations is studied under rebalancing problem. The paper proposes a bottom-up cluster-based model to solve the static rebalancing problem in bike sharing systems. First, the spatial and temporal patterns of bike sharing trips in the network are investigated. Second, a similarity measure based on the trips between stations is defined to discover groups of correlated stations, using a hierarchical agglomerative clustering method. Third, two levels for rebalancing are assumed as intra-clusters and inter-clusters with the aim of keeping the balance of the network at the beginning of days. The intra-cluster level keeps the balance of bike distribution inside each cluster, and the inter-cluster level connects different clusters in order to keep the balance between the clusters. Finally, rebalancing tours are optimized according to the positive or negative balance at both levels of the intra-clusters and inter-clusters using a single objective genetic algorithm. The rebalancing problem is modeled as an optimization problem, which aims to minimize the tour length. The proposed model is implemented in one week of bike sharing trip data set in Chicago, USA. Outcomes of the model are validated for two subsequent weekdays. Analyses show that the proposed model can reduce the length of the rebalancing tour by 30%.
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Bruck, Bruno P., Fábio Cruz, Manuel Iori, and Anand Subramanian. "The Static Bike Sharing Rebalancing Problem with Forbidden Temporary Operations." Transportation Science 53, no. 3 (May 2019): 882–96. http://dx.doi.org/10.1287/trsc.2018.0859.
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This paper introduces and solves the static bike rebalancing problem with forbidden temporary operations. In this problem, one aims at finding a minimum cost route in which a vehicle performs a series of pickup and delivery operations while satisfying demand and capacity constraints. In addition, a vehicle can visit stations multiple times but cannot use them to temporarily store or provide bikes. Apart from bike rebalancing, the problem also models courier service transportation and repositioning of inventory between retail stores, where temporary operations are frequently disliked because they require additional manual work and service time. We present some theoretical results concerning problem complexity and worst-case analysis, and then propose three exact algorithms based on different mathematical formulations. Extensive computational results on instances involving up to 80 stations show that an exact algorithm based on a minimal extended network produces the best average results. The online appendix is available at https://doi.org/10.1287/trsc.2018.0859 .
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Zhang, Chenyan, and Huiyu Zhou. "The study of Coopetition between Public Bus and Bike Sharing based on Environmental Protection." E3S Web of Conferences 136 (2019): 04015. http://dx.doi.org/10.1051/e3sconf/201913604015.
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Recently, the traditional travel modes and public transportation system in urban areas have undergone some subtle changes under the impact of shared bikes, especially for public bus, which is the most impacted by the shared bikes. Therefore, this paper mainly aims at studying the impact of shared bicycles on the public bus from both competitive and cooperative perspectives. More specifically, this study will explore the coopetition relationship between these two modes from travellers’ behaviour perspective. An SP survey has been conducted on traveller in Beijing and a Multinomial Logit model was adopted to quantitatively analyse the effect of various factors on travellers’ modal choice between bus and shared bikes. In this study, the estimation results show that the travel distance, road infrastructure, and travelers’ psychological factors all suggest a competition between bus and bike sharing. On the contrary, distance between bus transfer stations will also lead to modal cooperation. Finally, some policy implications have been proposed to better facilitate public transports and promote the sustainable development of whole urban transport system.
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Shvartsblat, Steve, Mary Kochie, Philip Harber, and John Howard. "Fatal rat bite fever in a pet shop employee." American Journal of Industrial Medicine 45, no. 4 (2004): 357–60. http://dx.doi.org/10.1002/ajim.10359.
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Zguira, Yosra, Hervé Rivano, and Aref Meddeb. "Internet of Bikes: A DTN Protocol with Data Aggregation for Urban Data Collection." Sensors 18, no. 9 (August 27, 2018): 2819. http://dx.doi.org/10.3390/s18092819.
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Intelligent Transport Systems (ITS) are an essential part of the global world. They play a substantial role for facing many issues such as traffic jams, high accident rates, unhealthy lifestyles, air pollution, etc. Public bike sharing system is one part of ITS and can be used to collect data from mobiles devices. In this paper, we propose an efficient, “Internet of Bikes”, IoB-DTN routing protocol based on data aggregation which applies the Delay Tolerant Network (DTN) paradigm to Internet of Things (IoT) applications running data collection on urban bike sharing system based sensor network. We propose and evaluate three variants of IoB-DTN: IoB based on spatial aggregation (IoB-SA), IoB based on temporal aggregation (IoB-TA) and IoB based on spatiotemporal aggregation (IoB-STA). The simulation results show that the three variants offer the best performances regarding several metrics, comparing to IoB-DTN without aggregation and the low-power long-range technology, LoRa type. In an urban application, the choice of the type of which variant of IoB should be used depends on the sensed values.
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Yang, Hong, Kun Xie, Kaan Ozbay, Yifang Ma, and Zhenyu Wang. "Use of Deep Learning to Predict Daily Usage of Bike Sharing Systems." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 36 (October 6, 2018): 92–102. http://dx.doi.org/10.1177/0361198118801354.
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The use of bikes among stations is often spatiotemporally imbalanced, causing many problems in daily operations. Predictively knowing how the system demand evolves in advance helps improve the preparedness of operational schemes. This paper aims to present a predictive modeling approach to analyze the use of bicycles in bike sharing systems. Specifically, a deep learning (DL) approach using the convolutional neural networks (CNNs) was proposed to predict the daily bicycle pickups at both city and station levels. A numerical study using data from the Citi Bike system in New York City (NYC) was performed to assess the performance of the proposed approach. Other than the historical records, relevant information like weather was also incorporated in the modeling process. The modeling results show that the proposed approach can achieve improved predictive performance in both city- and station-level analyses, confirming the merits of the proposed method against other baseline approaches. In addition, including information from neighboring stations into the models can help improve the performance of station-level prediction. The predictive performance of the CNN was also found to be related to parameters such as temporal window, number of neighboring stations, learning ratio, patch size, and the inclusion of additional data such as drop-offs. Thus, the implementation of the proposed models requires necessary calibration to determine appropriate parameters for a given bike sharing system.
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Choi, Yongrok, and Eun Jin Choi. "Sustainable Governance of the Sharing Economy: The Chinese Bike-Sharing Industry." Sustainability 12, no. 3 (February 7, 2020): 1195. http://dx.doi.org/10.3390/su12031195.
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Socialist countries, such as China, have stressed the importance of an equitable society where citizens work together. Thus, the sharing economy (e.g., the bike-sharing industry) could be one of the challenges determining the future of China, as the initial bubble of the bike-sharing industry collapsed in 2017, with many problems stemming from the users’ deposits that were lost and the depletion of the investment funds, resulting in numerous malfunctioning bikes every day. This paper evaluates the bike-sharing industry in terms of sustainable governance in the future and identifies its factors. Therefore, we use the structural equation model based on survey questionnaires and find that most of the input variables of the perceived rational (PRV) and emotional values (PEV), perceived risk (PR), and externalities (EXT) are not very successful in promoting the sustainable governance of the bike-sharing industry. However, using the bootstrapping simulation approach, we find that the role of modulators such as satisfaction and sustainable management factors are statistically significant. The modulating effect of a user’s satisfaction on the intention of continuous use based on all four inputs of PRV (0.304), PEV (0.298), PR (−0.156), and EXT (0.263), as well as the other indirect variables of sustainable management, such as environmental factors (0.284), is shown to be statistically significant. Based on these modulating effects, we conclude that the sharing economy, represented by the bike-sharing industry, could be one of the most important business cases for the future of China, but only if it is strongly supported by the public. Therefore, to help the industry get out of its current slump, we propose that the bike-sharing companies put in more diverse efforts to employ multi-use types of innovation with practical benefits such as coupons for the nearest shops, and social functions that enhance the quality of life such as mileage contribution from bike sharing for disabled people. Evidently, the Chinese government should eliminate “the over-supply issues” through appropriate market governance and increase its efforts toward a better public–private partnership (PPP), as the sharing economy should be based on the harmonization of all interest groups to eventually create value.
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WEBB, ERIC RUSSELL. "Show devant! English fetishization in Ironman France." Journal of French Language Studies 22, no. 3 (May 9, 2012): 447–66. http://dx.doi.org/10.1017/s0959269512000178.
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ABSTRACTThis paper examines the use of English-origin forms by Ironman France participants, with focus given to those having a widely used French equivalent (e.g. la finish and le bike). Investigation centres on print media, online discussion forums, and participant interviews. Innovative borrowings are argued to derive from a fetishization of English along the lines of Kelly Holmes (1997, 2000), whereby connotation is equally or more important than reference. It is further suggested that participants employ these innovative forms to distinguish themselves and solidify group identity, constituting a sort of sociolinguistic niche.
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Rumpa, Lantana Dioren. "DESAIN DAN IMPLEMENTASI INSTRUMEN DIGITAL PENGUKUR KECEPATAN, JARAK DAN PEMBAKARAN KALORI PADA SEPEDA GUNUNG BERBASIS MIKROKONTROL ATMEGA32." Journal Dynamic Saint 2, no. 2 (December 14, 2017): 326–37. http://dx.doi.org/10.47178/dynamicsaint.v2i2.103.
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Bicycle is one of the most popular transportation and in Indonesia there are still many people used it. Static bike or stationary bicycle is one of many kind of bicycle and people used it in indoor room. Static bike has an electronic panel that could help people who used it to know how far the distance, what abaout their speed and how many calories they have burned. Many people said that static bike is more fun and more interesting than outdoor bicycle especially from mountain bike because the static bike has the electronic panel. The electronic panel from static bike will be used on mountain bike so it can be more interresting as static bike. Microcontroller will used as minicomputer to processing all data from magnetic sensor that show the rotation of bike’s tires and then the microcontroller will show the result on seven segment display about the distances, the speed, and the calories burned.
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Ma, Xinwei, Ruiming Cao, and Jianbiao Wang. "Effects of Psychological Factors on Modal Shift from Car to Dockless Bike Sharing: A Case Study of Nanjing, China." International Journal of Environmental Research and Public Health 16, no. 18 (September 14, 2019): 3420. http://dx.doi.org/10.3390/ijerph16183420.
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The emergence of dockless bike sharing in recent years has reduced the usage of private cars, especially usage for short-distance trips (within 2 km). In this paper, a modified technology acceptance model (TAM) is proposed to investigate from the psychological perspective drivers’ willingness to shift to dockless bike sharing. The modified TAM includes the perceived usefulness of dockless bike sharing, perceived ease-of-use of dockless bike sharing, perceived health of dockless bike sharing, attitudes toward dockless bike sharing, and willingness to shift to dockless bike sharing. Data are obtained through offline communications with car drivers. The results show that two-thirds of car drivers are willing to use dockless bike sharing in short-distance trips. Perceived health, perceived ease-of-use, and perceived usefulness have significant positive effects on people’s attitudes toward dockless bike sharing. As expected, people’s attitudes toward dockless bike sharing are positively correlated with their willingness to shift. Policy implications are discussed to prompt the modal shift from private cars to dockless bike sharing according to the results.
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Guo, Yanyong, Yao Wu, Jian Lu, and Jibiao Zhou. "Modeling the Unobserved Heterogeneity in E-bike Collision Severity Using Full Bayesian Random Parameters Multinomial Logit Regression." Sustainability 11, no. 7 (April 8, 2019): 2071. http://dx.doi.org/10.3390/su11072071.
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Understanding the risk factors of e-bike collisions can improve e-bike riders’ safety awareness and help traffic professionals to develop effective countermeasures. This study investigates risk factors that significantly contribute to the severity of e-bike collisions. Two months of e-bike collision data were collected in the city of Ningbo, China. A random parameters multinomial logit regression (RP-MNL) is proposed to account for the unobserved heterogeneity across observations. A fixed parameters multinomial logit regression (FP-MNL) is estimated and compared with the RP-MNL under the Bayesian framework. The full Bayesian approach based on Markov chain Monte Carlo simulation is employed to estimate the model parameters. Both parameter estimates and odds ratio (OR) are used to interpret the impact of risk factors on the severity of e-bike collisions. The model comparison results show that RP-MNL outperforms FP-MNL, indicating that accommodating the unobserved heterogeneity across observations could improve the model fit. The model estimation results show that age, gender, e-bike behavior, license plate, bicycle type, location, and speed limit are statistically significant and associated with the severity of e-bike collisions. Furthermore, four risk factors, i.e., gender, e-bike behavior, bicycle type, and speed limit, are found to have heterogeneous effects on severity of e-bike collisions, appearing in the form of random parameters in the statistical model.
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Guo, Yanyong, Jibiao Zhou, Yao Wu, and Jingxu Chen. "Evaluation of Factors Affecting E-Bike Involved Crash and E-Bike License Plate Use in China Using a Bivariate Probit Model." Journal of Advanced Transportation 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/2142659.
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The primary objective of this study is to evaluate factors affecting e-bike involved crash and license plate use in China. E-bike crashes data were collected from police database and completed through a telephone interview. Noncrash samples were collected by a questionnaire survey. A bivariate probit (BP) model was developed to simultaneously examine the significant factors associated with e-bike involved crash and e-bike license plate and to account for the correlations between them. Marginal effects for contributory factors were calculated to quantify their impacts on the outcomes. The results show that several contributory factors, including gender, age, education level, driver license, car in household, experiences in using e-bike, law compliance, and aggressive driving behaviors, are found to have significant impacts on both e-bike involved crash and license plate use. Moreover, type of e-bike, frequency of using e-bike, impulse behavior, degree of riding experience, and risk perception scale are found to be associated with e-bike involved crash. It is also found that e-bike involved crash and e-bike license plate use are strongly correlated and are negative in direction. The result enhanced our comprehension of the factors related to e-bike involved crash and e-bike license plate use.
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Stenman, Lotta K., Reetta Holma, Helena Gylling, and Riitta Korpela. "Genetically obese mice do not show increased gut permeability or faecal bile acid hydrophobicity." British Journal of Nutrition 110, no. 6 (February 26, 2013): 1157–64. http://dx.doi.org/10.1017/s000711451300024x.
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Gut barrier dysfunction may lead to metabolic endotoxaemia and low-grade inflammation. Recent publications have demonstrated gut barrier dysfunction in obesity induced by a diet high in fat, and a pathogenetic role for luminal bile acids has been proposed. We aimed to investigate whether genetically obese mice develop increased gut permeability and alterations in luminal bile acids on a diet with a regular fat content. We used seven obese male ob/ob mice of C57BL/6J background and ten male wild-type (WT) mice of the same strain. Faeces were collected for bile acid analysis. Intestinal permeability was measured in an Ussing chamber upon euthanasia, using 4 kDa fluorescein isothiocyanate dextran, as per mille (‰, 1/1000) of translocated dextran. We analysed the liver expression of lipopolysaccharide-binding protein (LBP), as well as serum LBP (ELISA). Intestinal permeability was not affected by genetic obesity (jejunum: 0·234 (sem 0·04) ‰ for obese v. 0·225 (sem 0·03) ‰ for WT, P= 0·93; colon: 0·222 (sem 0·06) ‰ for obese v. 0·184 (sem 0·03) ‰ for WT, P= 0·86), nor was liver LBP expression (relative expression: 0·55 (sem 0·08) for obese v. 0·55 (sem 0·13) for WT, P= 0·70). Serum LBP was 2·5-fold higher in obese than in WT mice (P= 0·001). Obese mice had increased daily excretion of total bile acids, but their faecal bile acid hydrophobicity was unchanged. In conclusion, genetic obesity did not impair gut barrier function in mice on a regular chow diet, nor was faecal bile acid hydrophobicity affected.
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Ma, Liang, Xin Zhang, and Gao Shan Wang. "Identifying the Reasons why Users in China Recommend Bike Apps." International Journal of Market Research 59, no. 6 (November 2017): 767–86. http://dx.doi.org/10.2501/ijmr-2017-053.
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This study examines factors affecting users' intention to recommend bike-sharing apps from the perspective of internal and external benefits perception. Since the end of 2016, bike sharing has suddenly taken off in China, and competition is fierce. Bike-sharing users' intention to recommend bike apps is particularly important as it can help operators attract more potential users. However, little research to date has focused on bike-sharing users' intention to recommend bike apps in the Chinese context. This study aims to fill this research gap using structural equation modelling. Data were collected from 209 bike-sharing app customers and the results show the following key findings: (1) the usefulness of the bike-sharing app is the most important factor contributing to users' intention to recommend, followed by economic incentive and ease of use; (2) users' trust that interacts with perceived ease of use has positive effect on users' intention to recommend, while users' trust that interacts with economic incentive has negative effect on users' intention to recommend. Implications for researchers and practice are discussed.
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Yu, Zhuoran, Yimeng Duan, Shen Zhang, Xin Liu, and Kui Li. "A Spatiotemporal Prediction Model for Regional Scheduling of Shared Bicycles Based on the INLA Method." Journal of Advanced Transportation 2021 (July 31, 2021): 1–10. http://dx.doi.org/10.1155/2021/4959504.
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Dock-less bicycle-sharing programs have been widely accepted as an efficient mode to benefit health and reduce congestions. And modeling and prediction has always been a core proposition in the field of transportation. Most of the existing demand prediction models for shared bikes take regions as research objects; therefore, a POI-based method can be a beneficial complement to existing research, including zone-level, OD-level, and station-level techniques. Point of interest (POI) is the location description of spatial entities, which can reflect the cycling route characteristics for both commuting and noncommuting trips to a certain extent, and is also the main generating point and attraction point of shared-bike travel flow. In this study, we make an effort to model a POI-level cycling demand with a Bayesian hierarchical method. The proposed model combines the integrated nested Laplace approximation (INLA) and random partial differential equation (SPDE) to cope with the huge computation in the modeling process. In particular, we have adopted the dock-less bicycle-sharing rental records of Mobike as a case study to validate our method; the study area was one of the fastest growing urban districts in Shanghai in August 2016. The operation results show that the method can help better understand, measure, and characterize spatiotemporal patterns of bike-share ridership at the POI level and quantify the impact of the spatiotemporal effect on bicycle-sharing use.
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Zhai, Liu, Du, and Wu. "Fleet Size and Rebalancing Analysis of Dockless Bike-Sharing Stations Based on Markov Chain." ISPRS International Journal of Geo-Information 8, no. 8 (July 29, 2019): 334. http://dx.doi.org/10.3390/ijgi8080334.
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In order to improve the dynamic optimization of fleet size and standardized management of dockless bike-sharing, this paper focuses on using the Markov stochastic process and linear programming method to solve the problem of bike-sharing fleet size and rebalancing. Based on the analysis of characters of bike-sharing, which are irreducible, aperiodic and positive-recurrence, we prove that the probability limits the state (steady-state) of bike-sharing Markov chain only exists and is independent of the initial probability distribution. Then a new “Markov chain dockless bike-sharing fleet size solution” algorithm is proposed. The process includes three parts. Firstly, the irreducibility of the bike-sharing transition probability matrix is analyzed. Secondly, the rank-one updating method is used to construct the transition probability random prime matrix. Finally, an iterative method for solving the steady-state probability vector is therefore given and the convergence speed of the method is analyzed. Furthermore, we discuss the dynamic solution of the bike-sharing steady-state fleet size according to the time period, so as improving the practicality of the algorithm. To verify the efficiency of this algorithm, we adopt the linear programming method for bicycle rebalancing analysis. Experiment results show that the algorithm could be used to solve the disordered deployment of dockless bike-sharing.
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Rogers, Wendy A., Heather Draper, and Stacy M. Carter. "Evaluation of artificial intelligence clinical applications: Detailed case analyses show value of healthcare ethics approach in identifying patient care issues." Bioethics 35, no. 7 (May 28, 2021): 623–33. http://dx.doi.org/10.1111/bioe.12885.
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Jin, Xueting, and Daoqin Tong. "Station-Free Bike Rebalancing Analysis: Scale, Modeling, and Computational Challenges." ISPRS International Journal of Geo-Information 9, no. 11 (November 19, 2020): 691. http://dx.doi.org/10.3390/ijgi9110691.
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In the past few years, station-free bike sharing systems (SFBSSs) have been adopted in many cities worldwide. Different from conventional station-based bike sharing systems (SBBSSs) that rely upon fixed bike stations, SFBSSs allow users the flexibility to locate a bike nearby and park it at any appropriate site after use. With no fixed bike stations, the spatial extent/scale used to evaluate bike shortage/surplus in an SFBSS has been rather arbitrary in existing studies. On the one hand, a balanced status using large areas may contain multiple local bike shortage/surplus sites, leading to a less effective rebalancing design. On the other hand, an imbalance evaluation conducted in small areas may not be meaningful or necessary, while significantly increasing the computational complexity. In this study, we examine the impacts of analysis scale on the SFBSS imbalance evaluation and the associated rebalancing design. In particular, we develop a spatial optimization model to strategically optimize bike rebalancing in an SFBSS. We also propose a region decomposition method to solve large-sized bike rebalancing problems that are constructed based on fine analysis scales. We apply the approach to study the SFBSS in downtown Beijing. The empirical study shows that imbalance evaluation results and optimal rebalancing design can vary substantially with analysis scale. According to the optimal rebalancing results, bike repositioning tends to take place among neighboring areas. Based on the empirical study, we would recommend 800 m and 100/200 m as the suitable scale for designing operator-based and user-based rebalancing plans, respectively. Computational results show that the region decomposition method can be used to solve problems that cannot be handled by existing commercial optimization software. This study provides important insights into effective bike-share rebalancing strategies and urban bike transportation planning.
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Yu, Kui, and Changyue Qu. "Prediction and optimization of sharing bikes queuing model in grid of Geohash coding." Measurement and Control 53, no. 7-8 (June 7, 2020): 1250–66. http://dx.doi.org/10.1177/0020294019877521.
Full textAbstract:
Dockless bike-sharing systems provide parking anywhere feature and environment-friendly approach for commuter. It is booming all over the world. Different from dockless bike-sharing systems, for example, previous studies focus on rental mode and docking stations planning. Yet, due to the fact that human mobility patterns of temporal and geographic lead to bike imbalance problem, we modeled human mobility patterns, predicted bike usage, and optimized management of the bike-sharing service. First, we proposed adaptive Geohash-grid clustering to classify bike flow patterns. For simplicity and rapid modeling, we defined three queuing models: over-demand, self-balance, and over-supply. Second, we improved adaptive Geohash-grid clustering-support vector machine algorithm to recognize self-balance pattern. Third, based on the result of adaptive Geohash-grid clustering-support vector machine, we proposed Markov state prediction model and Poisson mixture model expectation-maximization algorithm. Based on data set from Mobike and OFO, we conduct experiments to evaluate models. Results show that our models offer better prediction and optimization performance.
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Munkácsy, András, and Andrés Monzón. "Impacts of Smart Configuration in Pedelec-Sharing: Evidence from a Panel Survey in Madrid." Journal of Advanced Transportation 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/4720627.
Full textAbstract:
Despite the recently increasing research interest, this is one of the first studies employing a panel sample of users and nonusers to understand the bike-sharing phenomenon (N=205). On the basis of a novel surveying technique, a case study on the clients of the state-of-the-art bike-sharing scheme of Madrid (Spain) is presented. BiciMAD is a system of the latest generation, namely, multimodal demand responsive bike-sharing: a fleet of electric pedal-assisted bicycles (pedelecs) with an advanced technology and unique smart service configuration to tackle challenges that may hinder the promotion of cycling and bike-sharing in the city. A statistical test has verified that there is a moderate association between previous intention and actual use of bike-sharing (Cramer’s V = 0.25) and both barriers and motivators of further use have been identified. Indicators on mobility patterns show that although drawing primarily from other sustainable modes of transport, bike-sharing has increased mobility (total number and distance of trips) and especially active travel but decreased the perceived travel time.
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Wang, Tao, Sihong Xie, Xiaofei Ye, Xingchen Yan, Jun Chen, and Wenyong Li. "Analyzing E-Bikers’ Risky Riding Behaviors, Safety Attitudes, Risk Perception, and Riding Confidence with the Structural Equation Model." International Journal of Environmental Research and Public Health 17, no. 13 (July 2, 2020): 4763. http://dx.doi.org/10.3390/ijerph17134763.
Full textAbstract:
To identify and quantify the factors that influence the risky riding behaviors of electric bike riders, we designed an e-bike rider behavior questionnaire (ERBQ) and obtained 573 valid samples through tracking surveys and random surveys. An exploratory factor analysis was then conducted to extract four scales: riding confidence, safety attitude, risk perception, and risky riding behavior. Based on the exploratory factor analysis, a structural equation model (SEM) of electric bike riding behaviors was constructed to explore the intrinsic causal relationships among the variables that affect the risky e-bike riding behavior. The results show that the relationship between riding confidence and risky riding behavior is mediated by risk perception and safety attitudes. Safety attitude was found to be significantly associated with risky riding behaviors. Specifically, herd mentality is most closely related to safety attitudes, which means that those engaged in e-bike traffic management and safety education should pay special attention to riders’ psychological management and education. Risk perception has a direct path to risky riding behaviors. Specifically, stochastic evaluation and concern degree are significantly related to e-bike riders’ risk perception. The findings of this study provide an empirical basis for the creation of safety interventions for e-bike riders in China.
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Batan, I. Made Londen, Syifa, and Danny Prasetyo. "Flexible and Ergonomically Three Wheel Bike for Post Stroke Patient." Applied Mechanics and Materials 836 (June 2016): 14–19. http://dx.doi.org/10.4028/www.scientific.net/amm.836.14.
Full textAbstract:
This paper explains the new design of the three wheel bike for post-stroke patients as a equipment for physical therapy. The bike can be pedaled by foot and / or by hand simultaneously. Bike frame is made of aluminum alloy pipe and consists of front and rear frame. The front frame is equipped with a steering system that can regulate the moving of two wheels of diameter of 22 ". The rear frame is equipped with a fold mechanism, shock breaker, seat and chain stay pipes for clamping the rear wheel with diameter of 22 ". The rear frame is also equipped with a mechanism of transfer speed in three levels. Bike length is 1645 mm, width 615 mm and height 1035 mm. However, after folded the bike dimension became 725 mm long, 460 mm wide and 1035 mm high. By using CATIA software the strength frame material is simulated and analyzed. The bike design is evaluated from ergonomics aspect with RULA method. The proposed design is performed into a prototype. The prototype test is conducted. The result test show, that the bike is pedaled, either by hand or foot, strong, safe and comfortable to ride. In order to evaluate the design benefit, the pedal test is also conducted in various pedal velocities by 3 post stroke patients as respondent. During 6 minutes pedaling number of rider heartbeat is measured. The result shows all the number of heartbeat is not exceeded than 120 HR. That means the bike is enough light to pedal or the patient must not give extra power to ride the bike. Moreover, during 4 weeks therapy by cycling the bike, pedal velocity each respondents is increase significantly around 26-96%, this means the muscle contraction of respondents is reduce and developed bike can be used as alternative equipment for physical therapy of post stroke patient. Because light and foldable, the bike can be moved easily and put in the trunk of a car without problem.