公交网络中的乘客需求预测系统和方法

公共交通工具,尤其是公交车服务,可以减少私家车的使用和燃油消耗,缓解交通拥堵和环境污染状况。当乘坐公交车时,乘客不仅关心等车时间,更在乎公交车的拥挤程度,过度拥挤的公交车会导致乘客放弃乘坐。可见,准确、实时、可靠的乘客需求预测可以帮助公交公司决定合理的公交发车时间间隔,并且可以减少乘客的等车时间,这是人们急切需要的。基于实际公交系统的大量数据,提出一个面向移动用户的乘客需求预测系统。该系统包括服务器端的信息数据流处理和挖掘程序,以及客户端的移动应用程序。然而,公交网络中的乘客需求预测存在三大挑战:不均匀性、突发性和周期性。为了解决这些问题,提出了3种预测模型和1种基于滑动窗口的框架来预测乘客的数目。开发了一个原型系统,该系统可运行在多个版本的Android移动手机上,22个月的连续实验证明,该系统能够对公交网络中的864110项乘客需求进行精确预测,其准确度超过78%。     

基于CAN总线的移动机器人通信系统设计

近年来,对移动机器人的研究已成为热点,尤其是对移动机器人数据通信系统的研究。由于CAN总线技术具有网络功能,因此本文利用CAN总线构建了一个移动机器人的数据通信系统,使得机器人内部可以灵活地挂接多个功能模块。本文所设计的移动机器人具有动作模块、语音交互模块、避障与导航模块等。实验表明利用CAN总线技术可以提升移动机器人数据通信的可靠性和可扩展性。     

Predicting time-sharing in mobile interaction

The era of modern personal and ubiquitous computers is beset with the problem of fragmentation of the user’s time between multiple tasks. Several adaptations have been envisioned that would support the performance of the user in the dynamically changing contexts in which interactions with mobile devices take place. This paper assesses the feasibility of sensor-based prediction of time-sharing, operationalized in terms of the number of glances, the duration of the longest glance, and the total and average durations of the glances to the interaction task. The data used for constructing and validating the predictive models was acquired from a field study (N = 28), in which subjects performing mobile browsing tasks were observed for approximately 1 h in a variety of environments and situations. The predictive accuracy achieved in binary classification tasks was about 70% (about 20% above default), and the most informative sensors were related to the environment and interactions with the mobile device. Implications to the feasibility of different kinds of adaptations are discussed.     

Involving users early on in the design process: closing the gap between mobile information services and their users

Designing mobile information services, including mobile Internet services, mobile banking, interactive mobile television, location-based services etc. that capture a mass market has not been easy, and there have been many disappointments over the past years. There are still uncertainties with regard to the kinds of mobile services users want and need. We argue that users wants and needs depend on their context, which means that users should play an important role in the design process of mobile information services, through a structured approach in which developers and users work together. In this paper, we present a group-based approach to include the user early on in the design process in an efficient way. We have applied the group-based approach in three cases, i.e. mobile services for campus visitors, wireless applications for the process industry and services for crisis management. In all cases, involving users early on in the design process enabled the developers to gather useful information for designing mobile information services.     

A robust MPC approach for the rebalancing of mobility on demand systems

A control-oriented model for mobility-on-demand systems is here proposed. The system is first described through dynamical stochastic state-space equations, and then suitably simplified in order to obtain a control-oriented model, on which two control strategies based on Model Predictive Control are designed. The first strategy aims at keeping the expected value of the number of vehicles parked in stations within prescribed bounds; the second strategy specifically accounts for stochastic fluctuations around the expected value. The model includes the possibility of weighting the control effort, leading to control solutions that may trade off efficiency and cost. The models and control strategies are validated over a dataset of logged trips of ToBike, the bike-sharing systems in the city of Turin, Italy.     

An empirical study examining the perceptions and behaviours of security-conscious users of mobile authentication

The purpose of this study is to better understand, from an explorative qualitative perspective, the motivations and practices of highly security-conscious users of mobile authentication, and their underlying mental models of those behaviours. Mobile authentication studies have largely overlooked the mindset of these users in the upper bound of security experience, who have considered their behaviour in terms of detailed knowledge of mobile authentication risk. Twenty IT professionals who self-identified as security-conscious mobile device users, many with decades of intensive security-specific experience, were interviewed for this study regarding their opinions and experiences with mobile device authentication and security. These users described usability and situational impairment issues, as well as a deep concern for their identity and data security arising from highly contextual combinations of distrust towards underlying technologies and situational risk. Derived implications for development of security methods adapted to these informed perspectives are discussed and will be the basis for follow-on research comparing these findings with everyday users.     

Newspaper demand prediction and replacement model based on fuzzy clustering and rules

A problem that most newspaper companies encounter daily is how to predict the right number of newspapers to print and distribute among distinct selling points. The aim is to predict newspaper demand as accurately as possible to meet customer need and decrease loss, the number of newspaper offered but not sold. The right amount depends of the newspaper demand at different selling points and is a function of the geographical location and customer profile. Currently, demand prediction is based on values experienced in the past and on management knowledge. This paper suggests the use of predictive data mining techniques as a systematic approach to explore newspaper company database and improve predictions. Predictions require accurate forecast of the daily newspaper amount needed at each selling point. The focus of the paper is on a prediction method that uses fuzzy clustering for data base exploration and fuzzy rules together with performance scores of selling points for prediction. Experimental results using actual data show that the method is effective when compared with the current methodology, neural network-based predictors, and autoregressive forecasters. In particular, the predictive data mining technique improves on average 10% in comparison with the use of the existing approaches.     

基于二次分解重构策略的航空客流需求预测

考虑到航空客流需求序列的季节性、非线性和非平稳等特点,提出了一个基于二次分解重构策略的航空客流需求预测模型。首先,通过STL和自适应噪声互补集成经验模态分解（CEEMDAN）方法对航空客流需求序列进行二次分解,并根据数据复杂度和相关度的特征分析结果进行分量重构;然后,采用模型匹配策略分别选取自回归单整移动平均季节（SARIMA）、自回归单整移动平均（ARIMA）、核极限学习机（KELM）和双向长短期记忆（BiLSTM）网络模型对各重构分量进行预测,其中KELM和BiLSTM模型的超参数通过自适应树Parzen估计（ATPE）算法确定;最后,将重构分量预测结果进行线性集成。以北京首都国际机场、深圳宝安国际机场和海口美兰国际机场的航空客流数据作为研究对象进行了1步和多步预测实验,实验结果表明,与一次分解集成模型STL-SAAB相比,所提模型的均方根误差（RMSE）提升了14.98%～60.72%。可见以“分而治之”思想为指导,所提模型结合模型匹配和重构策略挖掘出了数据的内在发展规律,从而为科学预判航空客流需求变化趋势提供了新思路。     

Extent of private information disclosure on online social networks: An exploration of Facebook mobile phone users

The present study adopts the Communication Privacy Management theory and investigates the factors that influence the extent of private information disclosure of Facebook mobile phone users. Using a sample size of 488 adult mobile phone users, the study further investigates the differential impact of age on the extent of private information disclosure. Results from the logistic regressions run reveal that use of smartphones to access social networking sites, use of multiple social networks, and being female decrease the likelihood of private information disclosure. In addition, usability problems increase the likelihood of information disclosure by older adults. The analyses show no association between perceived benefit and private information disclosure.     

Integrated bus transit scheduling for the Beijing bus group based on a unified mode of operation

This paper presents an applied study of scheduling buses and drivers for the Beijing Bus Group (BJBUS), the largest bus company in China. This is pioneering research in China for bus transit scheduling using computers based on a unified mode of operation. It is anticipated that the research fruits and experiences obtained would be of benefit to other bus operators in China. The bus transit scheduling problem in BJBUS is first presented in the paper. The particular characteristics are pointed out, which are different from those in developed countries, while many are common in China. After a brief review and analysis of the appropriateness of some currently successful approaches, the paper focuses on reporting the solution ideas and methods for BJBUS, especially those developed to solve the specific problems of BJBUS, such as scheduling buses with built-in meal periods, multi-type bus scheduling, restricting drivers to one or two particular buses, etc. Finally, the implementation and computational results are reported before the concluding remarks.     

Predicting the adoption of mobile financial services: The impacts of perceived mobility and personal habit

Mobile financial services (MFS) have become a critical issue in the financial sectors. An expanding application of mobile commerce, MFS play an important role in managing customer relationships. Thus, we proposed a model that incorporates three external variables—perceived enjoyment, perceived mobility, and personal habit—into the technology acceptance model (TAM) to assess the antecedents that influence continued usage intention in MFS. In addition, we examined the moderating effect of gender on customer relationships. Structural equation modeling was used, and 368 MFS users were investigated. The findings revealed that perceived mobility, personal habit, perceived usefulness, and perceived ease of use are the major antecedents that influence continued usage intention in MFS. However, perceived enjoyment is not significantly associated with intention. Moreover, gender moderates the relationships between the variables in the proposed model. Perceived mobility affecting usage intention will be stronger for men than for women, whereas personal habit affecting usage intention will be stronger for women than for men.     

电梯群控系统交通需求的迭代学习预测方法

提出对时变垂直交通需求的智能化迭代学习预测方法.该方法采用最小二乘支持向量机技术,动态预测未来的交通需求及其变化规律.在此基础上,提出以电梯交通需求净增量及其变化率强度为依据的交通模式划分的新规则.通过构造滤波函数的方法获取交通需求变化的主要信息,对交通模式量化识别,得到主要交通模式区间的临界点.仿真实验表明了该方法的有效性.     

An effective offloading middleware for pervasive services on mobile devices

The practical success of pervasive services running in mobile wireless networks and devices relies on their ability to provide effective and efficient offloading support, so as to satisfy the increasing demand for mobile devices to run heavier applications (e.g. those running on desktop PCs). Offloading is an effective mechanism for leveraging the severity of resource constrained mobile devices by migrating some computing load to nearby resource-rich surrogates (e.g. desktop PCs, servers) on home networks or their extension. This paper proposes a light-weight and efficient offloading middleware, which provides runtime offloading services for resource constrained mobile devices. The middleware considers multiple types of resources (i.e. memory, CPU and bandwidth) and carries out application partitioning and partition offloading in an adaptive and efficient manner. The corresponding algorithms are presented. The evaluation outcomes indicate the effectiveness and efficiency of this service offloading solution.     

Frequency and recency context for the management and retrieval of personal information on mobile devices

As users store increasingly larger amounts of personal information on their mobiles, the task of retrieving such items (e.g., contacts) becomes more difficult. We show that users can be categorized by their communication patterns and that each category benefits differently from supporting contact management applications. By examining mobile user call logs, we show that it is possible to aid retrieval tasks using relatively simple heuristics and algorithms that describe usage context, using solely the dimensions of contact use frequency and recency. We compare and discuss the results of the proposed method applied on two different mobile datasets: a large dataset from NOKIA and a smaller dataset collected by ourselves.     

Exploring the impact of use context on mobile hedonic services adoption: An empirical study on mobile gaming in China

Unlike traditional technologies, the use of mobile technology is exposed to shifting use contexts. Use context has frequently been described as an important factor influencing the adoption of mobile innovations. However, empirical evidence about the impact of use context is limited. This paper investigated the effect of use context on the formation of users’ perceptions of mobile hedonic services by using mobile gaming as an example. Through the employment of structural equation modelling technology, an adoption model of mobile gaming is proposed and assessed based on results from 267 questionnaires. The results show that use context is the strongest predictor of mobile game adoption. It directly or indirectly affects all different perceptions of mobile gaming in significant ways, including perceived ease of use, perceived usefulness, perceived enjoyment, cognitive concentration, attitude and behavioral intention. Additionally, perceived usefulness, perceived enjoyment and cognitive concentration all have a positive influence on the attitudinal variables of mobile game acceptance. We concluded that the formation of people’s perceptions about mobile gaming is conditional and based on the special consideration of certain use contexts. Both theoretical and practical implications are discussed.     

Measurement development for cultural characteristics of mobile Internet users at the individual level

Culture plays an important role in how an information technology is developed and used. However, few studies attempt to identify the cultural traits most relevant to the specific technology being examined. The main purpose of this study is to develop measures for cultural characteristics of individual users with a specific information technology, the mobile Internet. We propose measures for four cultural characteristics important in the context of the mobile Internet, which are expected to be widely used in the future. The proposed measures were verified empirically through online surveys conducted in seven countries. The results indicate that the measures have high validity and reliability, as well as comparability among the seven countries. The paper ends with a discussion of the study’s limitations and implications.     

A modified gradient projection algorithm for solving the elastic demand traffic assignment problem

This paper develops a path-based traffic assignment algorithm for solving the elastic demand traffic assignment problem (EDTAP). A modified path-based gradient projection (GP) method combined with a column generation is suggested for solving the equivalent excess-demand reformulation of the problem in which the elastic demand problem is reformulated as a fixed demand problem through an appropriate modification of network representation. Numerical results using a set of real transportation networks are provided to demonstrate the efficiency of the modified GP algorithm for solving the excess-demand formulation of the EDTAP. In addition, a sensitivity analysis is conducted to examine the effects of the scaling parameter used in the elastic demand function on the estimated total demand, number of generated paths, number of used paths, and computational efforts of the modified GP algorithm.     

The impact of distractions on the usability and intention to use mobile devices for wireless data services

Mobile technology has quickly become ingrained in society due to the flexibility of anywhere/anytime usage. However, factors associated with and that impact mobility, mobile users, and mobile use of products and services are still poorly understood. For example, even though distractions are ever present during everyday use of mobile devices, the nature and extent to which user perceptions and performance are affected by their presence is unknown. An empirical study was undertaken to investigate the impact of distractions and confirmation of pre-trial expectations on usability and its subsequent effect on consumers’ behavioral intention toward using a mobile device for wireless data services. Distractions were simulated in this study in the form of either user motion or environmental noise (i.e. background auditory and visual stimuli). A Structural Equation Modelling (SEM) analysis confirmed the impacts of distractions on efficiency and effectiveness, and in turn the users’ satisfaction and behavioral intention to use a mobile device for wireless data services. Support was also obtained for a mediating effect of post-trial confirmation of expectations between perceived performance and satisfaction. Implications of these findings for theory, practice, and future research are outlined.     

m-Brand loyalty and post-adoption variations for the mobile data services: Gender differences

This paper uses the value brand model in an attempt to determine the factors affecting post-adoption intentions through brand loyalty for the mobile data services. Data were collected online from 1266 respondents. The structural equation modeling was used to test the research model. The results show that post-adoption intentions are directly influenced by intangible attributes. Product deliverables and intangible attributes indirectly affect post-adoption intentions via m-brand loyalty. However, the results of current research do not show any effects of price on post-adoption intentions. The results also show genders differences in post-adoption intentions. Practical suggestions are provided. This paper advances our knowledge of post-adoption variations in business–consumer contexts and mobile business from the perspectives of utilitarian and non-utilitarian values of the mobile data services. This paper also contributes to the theory of post-adoption by offering across-gender examination.