Mobile Trajectory Research Articles

Privacy-Preserving Individual-Level COVID-19 Infection Prediction via Federated Graph Learning

Accurately predicting individual-level infection state is of great value since its essential role in reducing the damage of the epidemic. However, there exists an inescapable risk of privacy leakage in the fine-grained user mobility trajectories required by individual-level infection prediction. In this article, we focus on developing a framework of privacy-preserving individual-level infection prediction based on federated learning (FL) and graph neural networks (GNN). We propose Falcon , a F ederated gr A ph L earning method for privacy-preserving individual-level infe C tion predicti ON . It utilizes a novel hypergraph structure with spatio-temporal hyperedges to describe the complex interactions between individuals and locations in the contagion process. By organically combining the FL framework with hypergraph neural networks, the information propagation process of the graph machine learning is able to be divided into two stages distributed on the server and the clients, respectively, so as to effectively protect user privacy while transmitting high-level information. Furthermore, it elaborately designs a differential privacy perturbation mechanism as well as a plausible pseudo location generation approach to preserve user privacy in the graph structure. Besides, it introduces a cooperative coupling mechanism between the individual-level prediction model and an additional region-level model to mitigate the detrimental impacts caused by the injected obfuscation mechanisms. Extensive experimental results show that our methodology outperforms state-of-the-art algorithms and is able to protect user privacy against actual privacy attacks. Our code and datasets are available at the link: https://github.com/wjfu99/FL-epidemic .

Mobility and labor market trajectories of Ukrainian migrants to Poland in the context of the 2014 Russian invasion of Ukraine

ABSTRACT The 2014 Russian invasion of Ukraine resulted, among other things, in a dramatic increase in Ukrainian emigration to Europe, particularly to Poland. The article evaluates its consequences, by confronting trajectories of pre- and post- 2014 war male and female Ukrainian migrants to Poland. The comparisons combine mobility and migrants’ labor market paths linked to employment sectors. On data from surveys conducted in two Polish cities – Warsaw and Wrocław – in 2018-2019, we performed sequence analysis revealing seven clusters of trajectories, serving as a dependent variable in the multinomial regression analysis. We found that the war context contributed to the growth of permanency in Ukrainian migration, challenging a temporary mobility model observed in Ukraine-to-Poland migration for over two decades, which involves demographic consequences for Ukrainian society. In Poland, post-2014 war migrants are more likely than earlier cohorts to work in the new migrant niches, but contribute also to the revitalization of old ones. All of this contributes to structural changes in the Polish labor market. Importantly, we did not find evidence for a refugee penalty in economic integration, which we link to the mix of economic and humanitarian drivers of post-war Ukrainian migration to Poland.

Where do opportunity beliefs come from? Implications of intergenerational social mobility for beliefs about the distribution system in China

People’s understanding of the drivers of inequality is a function of their position in the social structure. Nevertheless, the ways in which intergenerational social mobility is associated with opportunity beliefs remain under researched. Recent findings in cultural sociology suggest that individuals seldom update their beliefs, and that settled dispositions lead people to reproduce their beliefs in their adulthood. This study used a probabilistic and representative survey of Chinese citizens to explore how intergenerational social mobility relates to opportunity beliefs. China presents an interesting context to explore this question, since Chinese society is considered to be highly unequal yet highly tolerant of social inequalities. Our results indicate a U-shaped relationship between social class and opportunity beliefs. The upper class and farmers exhibit stronger meritocratic beliefs than middle-classes. Moreover, upwardly and downwardly mobile individuals show greater weights for origin and destination, respectively. Thus, opportunity beliefs are explained by the social class where they rank lower. These findings suggest that when beliefs are updated through social mobility, they interact with the mobility trajectory. In addition, the stronger meritocratic beliefs of the farmers’ class and the greater weight of social origin for upwardly mobile individuals could help explain the dormant social volcano in China.

Path Planning and Trajectory Tracking Control for Two-Wheel Mobile Robot

The mobile robot is a system that can work in various environments. This means that the robot must be able to navigate without delay and avoid any obstacles placed within the boundaries of its movement. Designing mobile robots that can be intelligently managed and operate autonomously when traveling from one place to another requires at least two steps. To start with, path planning is required to prevent motion collisions. Tracking the robot's trajectory is a crucial second task. The primary goal of this study is to find the quickest and safest path between the two positions. In this work, we investigated the path planning of a mobile robot with dynamic, and dynamic obstacles with moving goal environments using RRT, BiRRT, and HA* algorithms. These algorithms are easy, computationally inexpensive, and simple to use. They have been chosen for numerous real-time path-planning applications. The DDMR's kinematic model has been utilized in this paper to control path tracking, and a PID controller has been proposed to reduce tracking deviations between the robot's actual route and the reference trajectory. This work introduced the PSO, FPA, CSA, SSA, BWOA, and proposed HBPO optimization techniques for obtaining PID parameters (k_p,k_i,k_d) for improved mobile robot trajectory tracking. The simulation results have been examined using three trajectory shapes: step, circular, and infinite. The simulation findings reveal that HA* outperforms the other algorithms by generating collision-free pathways that are smoother and shorter than their RRT and BiRRT equivalents. On the other hand, the proposed HBPO outperforms the other methods. The HBPO method converges quicker than the other proposed algorithms.

Who wants a reparative future? Social mobility beliefs, and young South African’s narrative positioning within the historic moral community

This paper explores how young South Africans think about the need for a reparative future through a consideration of their relationship to South Africa’s historic moral community. By historic moral community I draw on MacIntyre (2007), Sandel (2009), and Shotwell’s (2016) work to refer to the network of those from whom we inherit, and to whom we owe, an obligation – past, present, and future. This paper draws on data from a ten-month classroom ethnography in Cape Town. The ethnography looked at four Grade 9 history classrooms in four racially distinct schools and included multiple interviews with between four and six students from each class (n = 20) over the course of the year. Data collection focussed on how the legacies of apartheid were taught, and how students learned to use history to make sense of their personal circumstances and contemporary society. It also explored students’ narratives regarding their own social mobility trajectories, how they perceived the effects of apartheid on their own lives, and attitudes regarding the need for reparative action in light of apartheid. The data demonstrated not only the diversity of attitudes towards reparative futures that exist among South African youth, but also suggests that young people who narrate their life trajectories as being intertwined with South Africa’s historic moral community both advocate for collective responsibility for past injustice, and feel a sense of agency over their future social mobility.

An Improved BLG Tree for Trajectory Compression with Constraints of Road Networks

With the rising popularity of portable mobile positioning equipment, the volume of mobile trajectory data is increasing. Therefore, trajectory data compression has become an important basis for trajectory data processing, analysis, and mining. According to the literature, it is difficult with trajectory compression methods to balance compression accuracy and efficiency. Among these methods, the one based on spatiotemporal characteristics has low compression accuracy due to its failure to consider the relationship with the road network, while the one based on map matching has low compression efficiency because of the low efficiency of the original method. Therefore, this paper proposes a trajectory segmentation and ranking compression (TSRC) method based on the road network to improve trajectory compression precision and efficiency. The TSRC method first extracts feature points of a trajectory based on road network structural characteristics, splits the trajectory at the feature points, ranks the trajectory points of segmented sub-trajectories based on a binary line generalization (BLG) tree, and finally merges queuing feature points and sub-trajectory points and compresses trajectories. The TSRC method is verified on two taxi trajectory datasets with different levels of sampling frequency. Compared with the classic spatiotemporal compression method, the TSRC method has higher accuracy under different compression degrees and higher overall efficiency. Moreover, when the two methods are combined with the map-matching method, the TSRC method not only has higher accuracy but also can improve the efficiency of map matching.

User re-identification via human mobility trajectories with siamese transformer networks

User re-identification via human mobility trajectories with siamese transformer networks

An analysis of the nexus between youth urban mobility and COVID-19 trajectories for peace and development in Africa: Perspectives from Tanzania

The outbreak of the COVID-19 pandemic in 2019 posed prominent public policy concerns. It posed many unanswered questions, especially among the youth who require social protection in different contexts. The pandemic spread over 200 countries worldwide, infecting over 640 million individuals and resulting in the deaths of over 6.5 million people. However, the pandemic has a similar fundamental consequence, marked by widespread inequality across households and individuals. It is estimated that its consequences might be more detrimental, particularly among the youth in low-income families like Tanzania. The country received significant global attention for its COVID-19 response during the first year of the pandemic since it did not share pandemic statistics, implement lockdowns, and question vaccine efficacy while emphasizing traditional medicines. Despite the progress made, the ripple effects of the pandemic are still felt in the country and will probably remain for a long and drive policies for generations to come. Still, there is scanty information about how the youth have been affected by the pandemic, particularly in urban areas, and relatively little is known about the relationships between youth, urban mobility, and COVID-19 trajectories for peace and development in the country. This chapter uses Tanzania as a case study to assess the nexus between youth, urban mobility, and COVID-19 trajectories for African peace and development. The chapter relied on secondary data collected through a systematic review. Content analysis was applied to analyze the data. The chapter reveals several studies on youth and COVID-19 in Tanzania. Nevertheless, these studies are very few. Like other parts of Africa and the world over, COVID-19 has significantly impacted the youth in Tanzania. It also revealed determinants and challenges, like social, economic, health, mental, and learning effects, of urban youth mobility in the face of COVID-19. Since the COVID-19 pandemic has largely affected the lives of youth, this chapter provides relevant information that will prompt responsible authorities to adopt effective response measures for addressing the pandemic for enhanced peace and development in Tanzania and Africa.

Intra-generational social mobility and mortality among older men in the Concord Health and Ageing in Men Project: A cohort study

ObjectivesWe examined associations between intra-generational social mobility (reflected in life-course socioeconomic trajectories) and mortality, among older men. MethodsData came from a prospective Australian community-based cohort of older men. Social mobility was defined by socioeconomic indicators from three points in the life-course: educational attainment (late adolescence-early adulthood), occupation (mid-life), and current sources of income (older age). We defined indicators of social mobility trajectory (6 categories; reflecting the direction of social mobility) and social mobility status (2 categories; mobile or non-mobile). We used Cox regression to examine associations with mortality, adjusting for age, country of birth, and living arrangement. ResultsWe followed 1568 men (mean age 76.8, SD 5.4) for a mean duration of 9.1 years, with 797 deaths recorded. Moving upward was the predominant social mobility trajectory (36.0%), followed by mixed trajectories (25.1%), downward (15.1%), stable low (12.2%), stable high (7.6%), and stable middle (4.0%). Men with downward (Hazard ratio 1.58, 95% CI 1.13 to 2.19) and stable low socioeconomic trajectories (1.77, 1.25 to 2.50) had higher mortality risks than men with stable high socioeconomic trajectories, while men with upward trajectories had similar risks to those with stable high trajectories. 76.2% of the participants were classified as having mobile status; no associations were evident between binary social mobility status and mortality. DiscussionsThese findings suggest cumulative and persistent exposure to disadvantaged socioeconomic conditions across the life-course, rather than social mobility, is associated with increased mortality. For each stage of the life-course, addressing socioeconomic disadvantage may reduce inequities in mortality.

A state-based inverse reinforcement learning approach to model activity-travel choices behavior with reward function recovery

Behaviorally oriented activity-travel choices (ATC) modeling is a principal part of travel demand analysis. Traditional econometric and rule-based methods require explicit model structures and complex domain knowledge. While several recent studies used machine learning models, especially adversarial inverse reinforcement learning (IRL) models, to learn potential ATC patterns with less expert-designed settings, they lack a clear representation of rational ATC behavior. In this study, we propose a data-driven IRL framework based on the maximum causal approach to minimize f-divergences between expert and agent state marginal distributions, which provides a more sample-efficient measurement. In addition, we specify a separate state-only reward function and derive an analytical gradient of the f-divergence objective with respect to reward parameters to ensure good convergences. The method can recover a stationary reward function, which assures the agent to get close to the expert behavior when training from scratch. We validate the proposed model using cellular signaling data from Chongqing, China by comparing with baseline models (behavior cloning, policy-based, and reward-based models) in aspects of policy performance comparison, reward recovery, and reward transfer tasks. The experiment results indicate that the proposed model outperforms existing methods and is relatively less sensitive to the number of expert demonstrations. Qualitative analyses are provided on the fundamental ATC preferences on different features given the reward function recovered from the observed mobility trajectories, and on the learning behaviors under different choices of f-divergence.

Rising and falling on the social ladder: The bidimensional social mobility beliefs scale.

Recent works in the field of Social Psychology have shown the importance of studying subjective social mobility from different perspectives. In the literature about subjective societal mobility, most of the research is focused on the mobility-immobility framing. However, several authors suggested studying social mobility beliefs effects differentiating according to mobility's trajectory, that is, upward (i.e., improving status over time) and downward (i.e., getting worse in status over time). The present research was motivated by the lack of measures that discriminate between beliefs in upward and downward societal mobility. Across two studies using different samples of the Spanish adult population, we examined both dimensions of social mobility beliefs and tested their predictive validity on other related constructs. In Study 1 (N = 164), with an EFA, we corroborated the independence between the two types of mobility. The internal structure was confirmed by a CFA in Study 2 (N = 400). Furthermore, it was shown that upward and downward mobility beliefs are differently related to other related constructs. The results from Studies 1-2 showed good convergent validity. In all correlations with the different constructs (attitudes towards inequality, meritocratic beliefs, justification of the economic system, and status anxiety) we found opposite direction effects for both types of societal mobility (upward and downward). The development of this new instrument can help to deepen our understanding of the psychosocial consequences of subjective social mobility, as well as to differentiate two processes that may have different consequences.

Intergenerational Social Mobility, Brain Structure, and Cognitive Trajectory: Findings from the Whitehall II Study

AbstractBackgroundPrevious studies on the effects of intergenerational social mobility on cognitive outcomes were not consistent, additionally, underlining brain anatomical variation is unclear. In the present study, we aim to examine the associations of social mobility with brain structure and cognitive trajectories in older adults.MethodThe study included 771 participants, ages 69.8 ±5.2 years, of the Whitehall II ‐ MRI substudy (2012‐2016) with data on their father’s occupation, their own occupation in mid‐life, lifestyle (smoking, drinking, physical activity, social activity, sleep disturbances, auditory difficulty, depression, obesity, hypertension), neuroimaging (T1 structural MRI) and cognitive abilities (global cognition, crystallized cognitive ability, and fluid intelligence). Social mobility was classified into stable high social class, stable low social class, upward mobility and downward mobility group based on occupational shifts from father. We used the ANCOVA tests to assess the association of social mobility with gray matter volume (GMV) and cortical thickness (CT) in various brain regions, and the growth curve modeling (GCM) to evaluate its relations to cognition over 20 years, adjusting for social lifestyle covariates and associated GMV/CT regions identified above.ResultSocial mobility was significantly related to 48 out of the 136 regions of GMV across the frontal lobe, limbic lobe, and temporal lobe; and to 4 out of the 68 regions of CT at the whole‐brain level. Stable high social class preserved the largest GMV and CT value; pair‐wise results suggest upward mobility preserved a larger GMV value than the downward mobility group (average diff. in cm3: 0.121, P<0.05); and similarly a larger CT value (average diff. in cm:0.029, P = 0.051). In GCMs, stable high social class (ref. downward mobility) had a higher entry score of fluid intelligence (b = 2.617, P<0.05), all other comparisons including the entry score and decline rate of cognitive abilities were non‐significant.ConclusionOur results suggest a lack of direct association between social mobility and trajectories of global cognition and crystallized cognitive ability; instead, an indirect effect through preserving the value of brain GMV and CT may occur. Additionally, an adverse causal relationship between social mobility and fluid intelligence might happen.

Intergenerational Social Mobility, Brain Structure, and Cognitive Trajectory: Findings from the Whitehall II Study

AbstractBackgroundPrevious studies on the effects of intergenerational social mobility on cognitive outcomes were not consistent, additionally, underlining brain anatomical variation is unclear. In the present study, we aim to examine the associations of social mobility with brain structure and cognitive trajectories in older adults.MethodsThe study included 771 participants, ages 69.8 ±5.2 years, of the Whitehall II ‐ MRI substudy (2012‐2016) with data on their father’s occupation, their own occupation in mid‐life, lifestyle (smoking, drinking, physical activity, social activity, sleep disturbances, auditory difficulty, depression, obesity, hypertension), neuroimaging (T1 structural MRI) and cognitive abilities (global cognition, crystallized cognitive ability, and fluid intelligence). Social mobility was classified into stable high social class, stable low social class, upward mobility and downward mobility group based on occupational shifts from father. We used the ANCOVA tests to assess the association of social mobility with gray matter volume (GMV) and cortical thickness (CT) in various brain regions, and the growth curve modeling (GCM) to evaluate its relations to cognition over 20 years, adjusting for social lifestyle covariates and associated GMV/CT regions identified above.ResultsSocial mobility was significantly related to 48 out of the 136 regions of GMV across the frontal lobe, limbic lobe, and temporal lobe; and to 4 out of the 68 regions of CT at the whole‐brain level. Stable high social class preserved the largest GMV and CT value; pair‐wise results suggest upward mobility preserved a larger GMV value than the downward mobility group (average diff. in cm3: 0.121, P<0.05); and similarly a larger CT value (average diff. in cm:0.029, P = 0.051). In GCMs, stable high social class (ref. downward mobility) had a higher entry score of fluid intelligence (b = 2.617, P<0.05), all other comparisons including the entry score and decline rate of cognitive abilities were non‐significant.ConclusionsOur results suggest a lack of direct association between social mobility and trajectories of global cognition and crystallized cognitive ability; instead, an indirect effect through preserving the value of brain GMV and CT may occur. Additionally, an adverse causal relationship between social mobility and fluid intelligence might happen.

Life course financial mobility and later‐life memory function and decline by gender and race/ethnicity: an intersectional analysis of a multi‐ethnic cohort study

AbstractBackgroundIntersectionality is a theoretical framework capturing joint aspects of social identity (e.g., Black Women experience racism and sexism), which may allow richer understanding of ADRD disparities. We investigated whether life course financial mobility may be differentially associated with later‐life memory function and rate of change across intersectional identities defined by gender and race/ethnicity.MethodData were from KHANDLE and STAR, harmonized cohorts of integrated healthcare system members in Northern California (n = 2,347). Life course financial mobility was defined using measures of financial capital in childhood and adulthood as “consistently high”, “low childhood, high adulthood”, “high childhood, low adulthood”, and “consistently low”. We clustered individuals into 32 strata representing intersectional identities of gender and race/ethnicity across life course financial mobility trajectories. Verbal episodic memory was assessed over three waves using the Spanish and English Neuropsychological Assessment Scales (SENAS). We used mixed‐effects linear regression models with individuals nested within intersectional identity strata, adjusted for early‐life confounders. Models with and without fixed effects of gender, race/ethnicity, and financial mobility were estimated to evaluate if the random effects of the 32 intersectional identity strata contributed variance to the memory intercepts and slopes beyond these additive fixed effects.ResultParticipant mean baseline age was 73 years; 38% were men, 62% were women; 17% were Asian, 48% were Black, 15% were Latinx, and 21% were White. Consistently high financial capital was positively associated with baseline later‐life memory (0.124 SD units; 95% CI: 0.010, 0.238), as was financial mobility from low childhood to high adulthood (0.099 SD units; 95% CI: ‐0.032, 0.230), albeit non‐significantly. Neither was associated with memory decline. In a model without fixed effects of gender, race/ethnicity, and financial mobility, intersectional identities defined by these three factors contributed to 12% of variance in later‐life memory. After adding fixed effects to the model, the impact of intersectional identities on memory variance was reduced to 0.2% (Figure 1).ConclusionConsistently high financial capital and upward financial mobility from childhood to adulthood have positive associations with later‐life memory at baseline, but not rate of change. These association are similar across intersectional identities defined by gender and race/ethnicity.

Powering the transition: examining factors influencing the intention to adopt electric vehicles

Purpose The purpose of the study is to examine the factors that influence people's intention to adopt electric vehicles (EVs). The study used an expanded theory of planned behaviour (TPB) along with the addition of perceived trust and consideration of future consequences (CFC).Design/methodology/approach The study is based on primary data collected from 282 respondents in Punjab through a questionnaire. The collected data were analysed using SPSS 26 and AMOS 24 to perform confirmatory factor analysis and structural equation modelling.Findings The empirical analysis indicates that attitude, subjective norms and perceived trust have a significant influence on the adoption intention (AI) of EVs.Research limitations/implications The implications provide policymakers and marketers with better insights into marketing EVs in the trajectory of sustainable mobility. Marketers should create focussed marketing materials that highlight the environmental ease of use, lower running costs and sophisticated technology of electric automobiles. The limitations of the study provide valuable insights for future researchers.Originality/value This is the first study that uses CFC with the TPB model in the context of AI of EVs specifically for the Punjab region.

Different paths, same destination? Mobility trajectories of Mainland PhD students during the COVID-19 pandemic at a Hong Kong University

This study considers the diverse mobility trajectories of students from Mainland China (MC) who have studied in the West and relocated to Hong Kong (HK) to pursue PhDs. Based on interview data and documentary evidence, it explores how various forms of power have molded these mobility trajectories during the COVID-19 pandemic. The findings highlight two distinct types of academic mobility: cross-border and intracity. These trajectories interconnect and overlap while influenced by different manifestations of power integral to students’ academic experiences. Furthermore, the study critically evaluates the concept of a ‘safe place’ by analyzing the interviewees’ physical mobility trajectories—both within HK and between MC and HK. It reveals that the power dynamics underpinning public health policies in MC and HK, the linguistic practices in HK, and the 2019 political protests collectively impact students’ sense of belonging in HK. The study highlights the significance of developing education-related soft power, as well as a campus culture that promotes equal dialogue and mutual understanding.

Early-life impairments, chronic health conditions, and income mobility.

Individuals who have congenital conditions or become disabled early in life tend to have poorer educational and occupational outcomes than non-disabled individuals. Disability is known to be a complex entity with multiple causations, involving, inter alia, physiological, social, economic, and cultural factors. It is established that social factors can influence educational and occupational attainment for disabled people, and current disability policy in many countries, particularly in the Global North, stress the importance of equality of opportunity. However, there is a scarcity of research that explores the specific degrees to which advanced welfare states contribute to the equalization of life chances for individuals with early-life impairments and chronic health conditions. In this study, we use a Norwegian sample of high-quality register data on individuals with vision loss, hearing loss, physical impairment, type 1 diabetes, asthma, and Down syndrome diagnosed early in life and compare their intergenerational income mobility trajectories with a random sample drawn from the country's entire population. We find that individuals' early-life diagnoses are linked to significantly worse income outcomes in adulthood than what is observed among the general population. We conclude that even in one of the most advanced egalitarian welfare states, such as Norway, much remains to be done to equalize life chances for individuals with early-life impairments and chronic health conditions.

Cumulative disadvantage during childhood: The association between moving and accumulated neighborhood deprivation over a child’s life course in the Netherlands

ABSTRACT While the importance of residential moves and neighborhood context for children is widely recognized, few studies examine childhood mobility and neighborhood context together and over time. Using a typology of mobility trajectories based on frequency, age, distance and change in population density, this study analyzes the interrelatedness between mobility trajectories and socioeconomic neighborhood composition throughout childhood. Using full-population register data, we follow children born in the Netherlands in 1999 until age 16. Local spatial autocorrelation analyses reveal concentrations of childhood mobility and neighborhood deprivation in cities. Focusing on children born in metropolitan areas, results indicate that children born in deprived neighborhoods are more likely to experience any move. Short-distance moves are associated with increased exposure and long-distance moves with less exposure to neighborhood deprivation. We argue we need a multidimensional longitudinal perspective to fully capture residential contexts to which children are exposed and enhance knowledge of childhood accumulations of disadvantage.

Statistical inference for complete and incomplete mobility trajectories under the flight-pause model.

We formulate a statistical flight-pause model (FPM) for human mobility, represented by a collection of random objects, called motions, appropriate for mobile phone tracking (MPT) data. We develop the statistical machinery for parameter inference and trajectory imputation under various forms of missing data. We show that common assumptions about the missing data mechanism for MPT are not valid for the mechanism governing the random motions underlying the FPM, representing an understudied missing data phenomenon. We demonstrate the consequences of missing data and our proposed adjustments in both simulations and real data, outlining implications for MPT data collection and design.

Decomposition of travel time expenditure through individual mobility trajectories based on mobile phone signaling data

The concept of travel time expenditure (TTE) or travel time budget (TTB) was developed approximately 60 years ago, and its stability issues have long been debated based on traditional household travel survey (HHTS) methods or less developed information and communication technologies (ICTs). Recent advances in mobile phone technologies have enabled the use of individuals’ mobility information at the disaggregation level. The objective of this study is to explore the TTE based on mobile phone signaling data (MPSD) collected from the residents in two different types of districts in South Korea. The results may produce better spatiotemporal precision than traditional household survey data because MPSD is generated when a mobile phone changes the cell coverage area and base transceiver stations (BTSs) or whenever the recording time interval set by the cellular service provider arrives. On the other hand, tremendous effort is needed to collect and clean up the raw data compared to data obtained using the conventional HHTS method. This paper presents data-cleaning processes and the results of a TTE calculation as a function of the day of weekday, age group, and region type. The processes and results of this study could be useful for modeling human mobility behavior using MPSD.