Mobility Profiles Research Articles

Information Transmission Bounds Between Moving Terminals

In networks of mobile autonomous agents, e.g. for data acquisition, we may wish to maximize data transfer or to reliably transfer a minimum amount of data, subject to quality of service or energy constraints. These requirements can be guaranteed through both offline node design/specifications and online trajectory/communications design. Regardless of the distance between them, for a stationary point-to-point transmitter-receiver pair communicating across a single link under average power constraints, the total data transfer is unbounded as time tends to infinity. In contrast, we show that if the transmitter/receiver is moving at any constant speed away from each other, then the maximum transmittable data is bounded. Although general closed-form expressions as a function of communication and mobility profile parameters do not yet exist, we provide closed-form expressions for particular cases, such as ideal free space path loss. Under more general scenarios we instead give lower bounds on the total transmittable information across a single link between mobile nodes.

New and emerging data forms in transportation planning and policy: Opportunities and challenges for “Track and Trace” data

High quality, reliable data and robust models are central to the development and appraisal of transportation planning and policy. Although conventional data may offer good ‘content’, it is widely observed that it lacks context i.e. who and why people are travelling. Transportation modelling has developed within these boundaries, with implications for the planning, design and management of transportation systems and policy-making. This paper establishes the potential of passively collected GPS-based “Track & Trace” (T&T) datasets of individual mobility profiles towards enhancing transportation modelling and policy-making. T&T is a type of New and Emerging Data Form (NEDF), lying within the broader ‘Big Data’ paradigm, and is typically collected using mobile phone sensors and related technologies. These capture highly grained mobility content and can be linked to the phone owner/user behavioural choices and other individual context. Our meta-analysis of existing literature related to spatio-temporal mobile phone data demonstrates that NEDF’s, and in particular T&T data, have had little mention to date within an applied transportation planning and policy context. We thus establish there is an opportunity for policy-makers, transportation modellers, researchers and a wide range of stakeholders to collaborate in developing new analytic approaches, revise existing models and build the skills and related capacity needed to lever greatest value from the data, as well as to adopt new business models that could revolutionise citizen participation in policy-making. This is of particular importance due to the growing awareness in many countries for a need to develop and monitor efficient cross-sectoral policies to deliver sustainable communities.

Examining human attitudes toward shared mobility options and autonomous vehicles

This paper presents a comprehensive analysis of people’s attitudes toward shared mobility options and autonomous vehicles (AVs), with a focus on the underlying patterns and potential determinants. A stated preference (SP) survey was designed and implemented in the U.S. Four sets of questions were included in the questionnaire, each focused on one unique aspect of user attitudes, including a) preferences for mobility options and lifestyle (such as overall view of driving, factors in mode choice decisions and technology engagement), b) perceived benefits and concerns of shared mobility option, c) reasons toward or against private vehicle ownership, and d) motivations for and desired features of AVs. A structural equations model was developed to identify latent attitudinal factors and examine the correlations between the latent attitudes (as the endogenous variables) and the observed covariates (including the socio-economic and demographic characteristics, and users’ current mobility profile, such as mode use frequency, travel distance, and trip fare). The model identified eleven latent factors that represent various aspects of attitudes toward AVs and shared mobility options. The findings could be used by policymakers and Transportation Network Companies (TNCs) to a) recognize the users’ latent attitudes, b) understand the underlying patterns of attitudes, c) implement plans and policies more efficiently, d) guide or influence users’ perceptions, and e) enhance travel behavior models. This study lays the foundation for further analysis on understanding user acceptance and adoption of these emerging mobility options, which is essential to estimate the likelihood and magnitude of behavior shifts in the era of automated, connected and shared mobility.

Impaired mobility and pressure ulcer development in older adults: Excess movement and too little movement-Two sides of the one coin?

To identify how activity and mobility lead to pressure ulcer development, using two objective assessments, one for mobility and one for early pressure ulcer detection. 150 older persons from long-term settings were followed up for 20days, using an observational, quantitative, prospective study design. The study was conducted in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology statement. Visual skin assessment and sub-epidermal moisture assessments were undertaken daily. Activity was measured using the Braden subscale. Further, a mobility profile of the participants was identified using a piezoelectric motion sensor which provided a "movement score" (mean number of movements/hour). Movement scores from 22 healthy participants were also measured to better understand the mobility profile in a healthy population. Pressure ulcer incidence using visual skin assessment was 12.7% (low movers=6.7%; high movers=6%) and 78.7% using sub-epidermal moisture assessment (low movers=40.0%; high movers=38.7%). Sub-epidermal moisture assessment detected pressure ulcers on average 8.2days before they appeared visually on the skin's surface. Pressure ulcer detection was 25 times greater using sub-epidermal moisture compared to visual skin assessment. Considering the results of the "movement level" assessment using the motion sensor technology, of all those who were determined to be immobile by Braden, 18.8% were assessed as high movers. Pressure ulcers occurred both in low and high movers, which was unexpected as a similar finding has not been previously reported in the literature. The traditional focus on low movers/immobile individuals may detract from the identification of those making an abnormally high frequency of unsafe movements. Pressure ulcer assessment can be enhanced through a combination of sub-epidermal moisture assessment and visual skin assessment, and through the identification of both individuals with impaired mobility and those abnormally high movements, such as among those who are agitated.

(Invited) Differential Hall Effect Metrology (DHEM) Sub-Nm Profiling and Its Application to Dopant Activation in n-Type Ge

With silicon CMOS technology approaching its limits due to continued device scaling, many potential new channel materials have been proposed. Germanium shows considerable promise due to having higher electron and hole mobilities compared to silicon. In addition, the electron and hole mobilities are similar, making it a viable option for CMOS technology. High performance Ge PMOS has been demonstrated, but NMOS has lagged behind due to the difficulty in making low resistance contacts to n-type Ge. Contact resistance is a strong function of the carrier concentration at the semiconductor surface, and it is extremely difficult to achieve high electron activation in Ge. Point defects in Ge are known to behave as acceptor sites and reduce the overall electron activation, particularly near the surface. Minimization of these defects is essential to achieving high performance Ge NMOS. Techniques such as fluorine passivation and co-doping with Sb and P have been shown to reduce the defect density and improve dopant activation, but the impact of these methods in the near-surface regime has largely been uncharacterized. Accurate analysis of dopant activation within 5 nm of the surface is critical to understanding the effectiveness of such processes on improving contact resistance.Differential Hall Effect Metrology (DHEM) is a powerful method that provides dopant activation depth profiles at sub-nm resolution. The method employs electrochemical means of reducing the electrically active thickness of a semiconductor film and determining the sheet resistance and mobility of the thinned down layer using Van der Pauw/Hall effect type measurements. Repeating this process and using differential equations, depth profiles of mobility and carrier concentration are obtained [1].We have previously used the ALProTM tool employing the DHEM technique to study the effect of Ge co-doping with Sb and P on near-surface dopant activation [2]. In Ge with only P-doping, the active dopant concentration was ~5x1018cm-3 at the surface despite the P chemical concentration being ~1x1020cm-3, indicating that only 5% of the implanted dopants were electrically active. With co-doping of Sb and P, the active electron concentration increased to ~2x1019cm-3 with a similar P chemical concentration. Prior work has shown similar increases in activation with co-doping but did not capture the significant decrease in electron concentration by 4x within 10 nm of the surface. Here, we further study the effects of the implantation and annealing process on near-surface dopant activation in n-type Ge. Samples were prepared by growing 3 µm thick epi-Ge layers on Si substrates. Sample 1 was capped with 20 nm SiO2 and Sample 2 was capped with 20 nm Al2O3 to minimize implant damage and control implant depth. Both samples were implanted first with Sb (dose: 6x1014cm-2, energy: 65 keV) followed by P (dose: 6x1014cm-2, energy: 90 keV). Post-implant anneal was done at 500°C for 10 s in N2 to activate the dopants. ALProTM and SIMS measurements were done to characterize active dopant concentration and total chemical dopant concentration, respectively.The Al2O3 capped sample (Sample 2) showed significantly lower dopant activation than the SiO2 capped sample (Sample 1) throughout the depth of the profile (Figure 1). Active electron concentration at the surface was lower by nearly an order of magnitude, decreasing from ~2x1019cm-3 to ~2x1018cm-3. Additionally, the peak concentration decreased from 1x1020cm-3 to 5x1019cm-3 at a depth of ~30 nm in both cases. The variations in the carrier profile for the Al2O3 capped sample also indicate greater process variation. SIMS profiles show that there is significant diffusion of Al into the Ge matrix after implant and anneal. Al chemical concentration is 1x1020cm-3 at the Ge surface and steadily decays up to a depth of more than 300 nm. This indicates that there is significant damage caused during the implantation process and the activation anneal is not enough to remove these defects. Al atoms then diffuse from the Al2O3 capping layer into the highly defective Ge substrate. Al is a p-type dopant in Ge and effectively counter dopes the Sb and P implants to reduce overall electron concentration in the Al2O3 capped sample. It is important to note the high resolution DHEM technique was able to resolve this important phenomenon right near the surface of the material.

Time, space, money, and social interaction: Using machine learning to classify people’s mobility strategies through four key dimensions

Previous activity-based studies have shown that behavioural outcomes are the result of complex and multidimensional processes. In this context, identifying and characterizing discrete mobility profiles through the classification of people’s behavior is particularly attractive. By facilitating the interpretation of complex, multidimensional processes, such an exercise could help to efficiently target transport policy decisions. The purpose of this paper is to identify mobility strategy profiles considering four key dimensions: time, space, money, and social interaction. Data from a seven-day activity, travel, expenditure, and social interaction diary applied to a sample of residents from the city of Concepción, Chile, is used. A two-step approach based on machine learning techniques is adopted. First, we use a Self-Organizing Map algorithm to identify seven distinct mobility strategies, each characterized by distinctive behaviors. These profiles are identified through 18 weekday and weekend daily behavior variables measuring the four key dimensions mentioned above, with an explicit focus on transport mode use. In the second step, we use a Decision Tree algorithm to profile the mobility strategies by means of personal and household sociodemographic variables. The results show interesting links among the dimensions of analysis within these profiles, such as connections between monetary expenditure on leisure and daily social interaction, and that profiles with higher private vehicle modal split tend to present higher levels of social interaction with people in their social network than public transit users.

Chemo-Hydrodynamic Patterns and Instabilities

By modifying a physical property of a solution like its density or viscosity, chemical reactions can modify and even trigger convective flows. These flows in turn affect the spatiotemporal distribution of the chemical species. A nontrivial coupling between reactions and flows then occurs. We present simple model systems of this chemo-hydrodynamic coupling. In particular, we illustrate the possibility of chemical reactions controlling or triggering viscous fingering, Rayleigh–Taylor, double-diffusive, and convective dissolution instabilities. We discuss laboratory experiments performed to study these phenomena and compare the experimental results to theoretical predictions. In each case we contrast the chemo-hydrodynamic patterns and instabilities with those that develop in nonreactive systems and unify the different dynamics in terms of the common features of the related spatial mobility profiles.

Quantification of transmitted energy and power for system services by battery electric vehicles based on real mobility and charging profiles

This study aims to separately quantify the application potential of electric vehicles for providing negative and positive system services. The data basis is the mobility and charging profiles of real battery electric vehicles. The vehicles only provide system services in the unused connection time with the charging infrastructure. The mobility offer for vehicle users is therefore not restricted. In addition, the power limitation by the energy grid and the efficiency losses through infrastructure and energy conversion depending on the energy direction are considered. The results show that battery electric vehicles can provide system service to a significant extent, especially in the period from late evening to the early morning hours.

Future Urban Charging Solutions for Electric Vehicles

The numbers of electric vehicles (EV) will increase as many countries perceive EVs as a solution to reduce the emissions of transportation and therefore incentivize their adoption. However, the deployment of public charging infrastructure is lagging behind that of EVs, which represents a potential barrier to their wide-scale adoption. The objective of this paper is to develop a comprehensive overview of potential EV charging solutions to be deployed in urban areas. Using a micro-Delphi approach, experts from transport, energy and urban planning were consulted and identified 15 realistic options for charging electric vehicles in urban environments by 2035. The solutions range from purely technical to more service oriented. Most of these solutions already exist today, although some remain at a very early stage of deployment. The five most likely options were on-street public charging points, charging at work, fast-charging stations, using building domestic plugs and semi-fast charging in public areas. When combined with the typical mobility and residential profiles, our results show that EV drivers will most likely rely on a mix of solutions, when they have no home chargers. As such, no breakthrough or major shift is expected in charging infrastructures, rather a scale-up of existing solutions. Our analysis concludes that urban charging options will be numerous and no single solution is expected to dominate as users with different EV user profiles will charge at different times and locations.

Mobile agent and ontology approach for web service discovery using QoS

Web services are meaningful only if potential users may find and execute them. Universal Description Discovery and Integration (UDDI) help businesses, organisations, and other web services providers to discover and reach to the service(s) by providing the URI of the WSDL file. However, it does not offer a mechanism to choose a web service based on its quality. The standard also lacks sufficient semantic description in the content of web services, this lack makes it difficult to find and compose suitable web services during analysis, search, and matching processes. In addition, a central UDDI suffers from one centralised point problem and the high cost of maintenance. To get around these problems, the authors propose in this paper a novel framework based on mobile agent, metadata catalogue and user profile for web services discovery in order to reduce the search space and increase the number of relevant services.

Salt bridges govern the structural heterogeneity of heme protein interactions and porphyrin networks: microperoxidase-11.

In this work, a proteolytic digest of cytochrome c (microperoxidase 11, MP-11) was used as a model to study the structural aspects of heme protein interactions and porphyrin networks. The MP-11 structural heterogeneity was studied as a function of the starting pH (e.g., pH 3.1–6.1) and concentration (e.g., 1–50 μM) conditions and adduct coordination. Trapped ion mobility spectrometry coupled to mass spectrometry (TIMS-MS) showed the MP-11 structural dependence of the charge state distribution and molecular ion forms with the starting pH conditions. The singly charged (e.g., [M]+, [M − 2H + NH4]+, [M − H + Na]+ and [M − H + K]+) and doubly charged (e.g., [M + H]2+, [M − H + NH4]2+, [M + Na]2+ and [M + K]2+) molecular ion forms were observed for all solvent conditions, although the structural heterogeneity (e.g., number of mobility bands) significantly varied with the pH value and ion form. The MP-11 dimer formation as a model for heme-protein protein interactions showed that dimer formation is favored toward more neutral pH and favored when assisted by salt bridges (e.g., NH4+, Na+ and K+vs. H+). Inspection of the dimer mobility profiles (2+ and 3+ charge states) showed a high degree of structural heterogeneity as a function of the solution pH and ion form; the observation of common mobility bands suggest that the different salt bridges can stabilize similar structural motifs. In addition, the salt bridge influence on the MP-11 dimer formations was measured using collision induced dissociation and showed a strong dependence with the type of salt bridge (i.e., a CE50 of 10.0, 11.5, 11.8 and 13.0 eV was observed for [2M + H]3+, [2M − H + NH4]3+, [2M + Na]3+ and [2M + K]3+, respectively). Measurements of the dimer equilibrium constant showed that the salt bridge interactions increase the binding strength of the dimeric species.

Floating Car Data mining: Identifying vehicle types on the basis of daily usage patterns

This paper presents a novel approach for exploring vehicle daily mobility patterns using Floating Car Data in the Paris region. The objective is to reveal vehicle types and analyze usage patterns on different roadway sub-classes. Firstly, mobility representative features are recovered to recognize vehicle activity contexts, which includes modeling single trip pattern in terms of time-window, traveling-distance, and speed; and building vehicle mobility profile of trip combinations. Based on that, a two-step clustering algorithm is developed to explore the constitution of trip patterns and cluster vehicle types. Characterization analysis is conducted to find out outstanding features of clustered groups, thus helping to categorize the vehicles behavioral types. As a result, 4 major vehicle types were identified over the Paris region with the 2 comparative leading groups as those mainly composed by morning-activity trips and long-distance trips. Then, statistical association assessment by Configural Frequency Analysis is employed to examine the usage intensity on different roadway classes of identified types. The association analysis reveals that the identified types have statistically significant differences in the usage of different roadway classes. Furthermore, this approach can be expected to provide more representative results with more generalized sampling by the development of connected vehicles.

First-principles study of BC3 monolayer as anodes for lithium-ion and sodium-ion batteries applications

In this paper we have studied the stability, mobility and voltage profile of alkali metal intercalated BC3 monolayer (MxBC3), for 0 < x ≤ 1 and M = Li, Na. Firstly, our calculations have the objective to identify the lower energy of Li and Na adsorption sites by using the density functional theory, then we calculate the minor diffusion energies of Na and Li on the surface of BC3 monolayer as shown by the total density of states of MxBC3 (M = Li, Na). Moreover, we showed that BC3 monolayer has changed his semiconductor character to metallic character after the adsorption of Li and Na on his surface. Importantly, we have demonstrated that BC3 monolayer has a higher theoretical capacity (582,63 mA h/g) as compared to Mo2C, VS2, MoS2, and graphite. Finally, we show that monolayer BC3 has a low average open-circuit voltage of 0.48 V for Li and 0.79 V for Na. These results highlight suggest that BC3 monolayer can be a promising anode material both for lithium-ion and sodium-ion batteries.

PRIMULE: Privacy risk mitigation for user profiles

The availability of mobile phone data has encouraged the development of different data-driven tools, supporting social science studies and providing new data sources to the standard official statistics. However, this particular kind of data are subject to privacy concerns because they can enable the inference of personal and private information. In this paper, we address the privacy issues related to the sharing of user profiles, derived from mobile phone data, by proposing PRIMULE, a privacy risk mitigation strategy. Such a method relies on PRUDEnce (Pratesi et al., 2018), a privacy risk assessment framework that provides a methodology for systematically identifying risky-users in a set of data. An extensive experimentation on real-world data shows the effectiveness of PRIMULE strategy in terms of both quality of mobile user profiles and utility of these profiles for analytical services such as the Sociometer (Furletti et al., 2013), a data mining tool for city users classification.

Differences in the intrinsic spatial dynamics of the chromatin contribute to cell differentiation.

Advances in chromosome conformation capture techniques as well as computational characterization of genomic loci structural dynamics open new opportunities for exploring the mechanistic aspects of genome-scale differences across different cell types. We examined here the dynamic basis of variabilities between different cell types by investigating their chromatin mobility profiles inferred from Hi-C data using an elastic network model representation of the chromatin. Our comparative analysis of sixteen cell lines reveals close similarities between chromosomal dynamics across different cell lines on a global scale, but notable cell-specific variations emerge in the detailed spatial mobilities of genomic loci. Closer examination reveals that the differences in spatial dynamics mainly originate from the difference in the frequencies of their intrinsically accessible modes of motion. Thus, even though the chromosomes of different types of cells have access to similar modes of collective movements, not all modes are deployed by all cells, such that the effective mobilities and cross-correlations of genomic loci are cell-type-specific. Comparison with RNA-seq expression data reveals a strong overlap between highly expressed genes and those distinguished by high mobilities in the present study, in support of the role of the intrinsic spatial dynamics of chromatin as a determinant of cell differentiation.

A flexible IPv6 mobility management architecture for SDN‐based 5G mobile networks

AbstractWith the advent of increasingly diverse services, applications, and use cases, the 5G mobility environment is expected to be highly heterogeneous. The distributed mobility management (DMM) is emerging as a promising approach for 5G, which provides decentralized handover and traffic management at the edge of the network. However, in order to meet the disparate mobility needs, the DMM process requires flexible design considerations. This paper presents a novel mobile node (MN) centered, software‐defined networking (SDN)–based flexible mobility management architecture, named adaptive multimode mobility management (A3M), which can adaptively operate in multiple modes. The proposed A3M architecture incorporates a novel handover mode selection phase among the traditional handover phases during which a suitable mode of handover operation is evaluated. This makes the A3M handover process adaptable to the varying mobility requirements of the MN and enables it to provide differentiated handover management for MNs with different mobility profiles. The performance analysis of A3M shows that it offers optimal handover performance in terms of primary handover performance metrics such as session disruption delay, packet losses, and signaling costs, compared to the popular network‐based DMM approaches.

OTFS-NOMA: An Efficient Approach for Exploiting Heterogenous User Mobility Profiles

This paper considers a challenging communication scenario, in which users have heterogenous mobility profiles, e.g., some users are moving at high speeds and some users are static. A new non-orthogonal multiple-access (NOMA) transmission protocol that incorporates orthogonal time frequency space (OTFS) modulation is proposed. Thereby, users with different mobility profiles are grouped together for the implementation of NOMA. The proposed OTFS-NOMA protocol is shown to be applicable to both uplink and downlink transmission, where sophisticated transmit and receive strategies are developed to remove inter-symbol interference and harvest both multi-path and multi-user diversity. Analytical results demonstrate that both the high-mobility and the low-mobility users benefit from the application of OTFS-NOMA. In particular, the use of NOMA allows the spreading of the high-mobility users’ signals over a large amount of time-frequency resources, which enhances the OTFS resolution and improves the detection reliability. In addition, OTFS-NOMA ensures that low-mobility users have access to bandwidth resources which in conventional OTFS-orthogonal multiple access (OTFS-OMA) would be solely occupied by the high-mobility users. Thus, OTFS-NOMA improves the spectral efficiency and reduces latency.

PKCε-dependent H-Ras activation encompasses the recruitment of the RasGEF SOS1 and of the RasGAP neurofibromin in the lipid rafts of embryonic neurons

The spatial organization of plasma membrane proteins is a key factor in the generation of distinct signal outputs, especially for PKC/Ras/ERK signalling. Regulation of activation of the membrane-bound Ras, critical for neuronal differentiation and highly specialized functions, is controlled by exchanges in nucleotides catalyzed by nucleotide exchange factors (GEFs) for GTP loading and Ras activation, and by Ras GTPase Activated Proteins (RasGAPs) that lead to activation of the intrinsic GTPase activity of Ras and thus its inactivation. PKCs are potent Ras activators yet the mechanistic details of these interactions, or the involvement of specific PKC isoforms are now beginning to be addressed. Even less known is the topology where RasGAPs terminate Ras activation. Towards this aim, we isolated lipid rafts from chick embryo neural tissue and primary neuronal cultures when PKCε is the prominent isoform and in combination with in vitro kinase assays, we now show that, in response the PKCε-specific activating peptide ψεRACK, an activated PKCε is recruited to lipid rafts; similar mobility was established when PKCε was physiologically activated with the Cannabinoid receptor 1 (CB1) agonist methanandamide. Activation of H-Ras for both agents was then established for the first time using in vivo RasGAP activity assays, which showed similar temporal profiles of activation and lateral mobility. Moreover, we found that the GEF SOS1, and the major neuronal RasGAP neurofibromin, a specific PKCε substrate, were both transiently significantly enriched in the rafts. Finally, our in silico analysis revealed a highly probable, conserved palmitoylation site adjacent to a CARC motif on neurofibromin, both of which are included only in the RasGAP related domain type I (GRDI) with the known high H-RasGAP activity. Taken together, these results suggest that PKCε activation regulates the spatial plasma membrane enrichments of both SOS1 and neurofibromin, thus controlling the output of activated H-Ras available for downstream signalling in neurons.

Depth profiles of damage creation and hardening in MgO irradiated with GeV heavy ions

The effect of irradiation with GeV heavy ions (U, Au, Bi) on the structure and mechanical properties of MgO single crystals was studied. The methods of nanoindentation, dislocation mobility, optical absorption and photoluminescence (PL) spectroscopy, X-ray diffraction and atomic force microscopy were used for damage characterization. The ion-induced increase of hardness and reduction of dislocation mobility was observed. The depth profiles of hardness, dislocation mobility and PL were investigated, and the contribution of electronic and nuclear loss mechanisms was confirmed. The efficiency of damage vs. average absorbed energy for heavy and light ions was compared. The change in the mechanism of plastic deformation at indentation was observed after severe irradiation due to the immobilization of dislocations by ion-induced extended defects. The results show that MgO single crystals maintain integrity and micro-plasticity at indentation, and exhibit improved hardness after irradiation with swift heavy ions at fluences up to 7 × 1013 ions/cm2.

Modeling and implement of mobile phone user location discrimination based on heuristic strategy

With the all-pervading mobile devices and continuing advancement of big data technologies, mobile phone data research has been gaining widespread popularity in the past few years. Dealing with the implausible location caused by cell handover phenomenon in the communication system is one key problem of user mobility profile building based on mobile phone call detail records (CDRs) data. In this paper, we propose a location discrimination model aiming at CDRs data, where heuristic strategies for the characteristic of the oscillation phenomenon from practical CDRs and handover categories are added to distinguish the stay points, passing points, and oscillating points. A whole month of CDRs data from one communication operator is employed to select parameters and validate the model on the Spark platform. The experiment results betray that the proposed model can identify the false locations effectively. Compared with the threshold models, the result of the proposed model is more reasonable both in the population aggregate level and individual level. Besides, the model can retain more user’s trajectory points than clustering algorithm, so it can improve the quality of user mobility modeling.