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Estimating activity patterns using spatio-temporal data of cell phone networks
, Article International Journal of Urban Sciences ; 2017 , Pages 1-18 ; 12265934 (ISSN) ; Shafahi, Y ; Sharif University of Technology
Abstract
The tendency towards using activity-based models to predict trip demand has increased dramatically over recent years. However, these models have suffered from insufficient data for calibration, and the intrinsic problems of traditional methods impose the need to search for better alternatives. This paper discusses ways to process cell phone spatio-temporal data in a manner that makes it comprehensible for traffic interpretations and proposes methods on how to infer urban mobility and activity patterns from the aforementioned data. The movements of each subscriber are described by a sequence of stops and trips, and each stop is labelled by an activity. The types of activities are estimated...
Estimating activity patterns using spatio-temporal data of cell phone networks
, Article International Journal of Urban Sciences ; Volume 22, Issue 2 , 2018 , Pages 162-179 ; 12265934 (ISSN) ; Shafahi, Y ; Sharif University of Technology
Routledge
2018
Abstract
The tendency towards using activity-based models to predict trip demand has increased dramatically over recent years. However, these models have suffered from insufficient data for calibration, and the intrinsic problems of traditional methods impose the need to search for better alternatives. This paper discusses ways to process cell phone spatio-temporal data in a manner that makes it comprehensible for traffic interpretations and proposes methods on how to infer urban mobility and activity patterns from the aforementioned data. The movements of each subscriber are described by a sequence of stops and trips, and each stop is labelled by an activity. The types of activities are estimated...
Estimating activity patterns using spatio-temporal data of cellphone networks
, Article MATEC Web of Conferences, 6 July 2016 through 10 July 2016 ; Volume 81 , 2016 ; 2261236X (ISSN) ; Shafahi, Y ; Sharif University of Technology
EDP Sciences
2016
Abstract
The tendency towards using activity-based models to predict trip demand has increased dramatically over recent years, but these models have suffered insufficient data for calibration. This paper discusses ways to process the cellphone spatio-temporal data in a manner that makes it comprehensible for traffic interpretations and proposes methods on how to infer urban mobility and activity patterns from the aforementioned data. Movements of each subscriber is described by a sequence of stays and trips and each stay is labeled by an activity. The type of activities are estimated using features such as land use, duration of stay, frequency of visit, arrival time to that activity and its distance...
An access and inference control model for time series databases
, Article Future Generation Computer Systems ; Volume 92 , 2019 , Pages 93-108 ; 0167739X (ISSN) ; Amini, M ; Sharif University of Technology
Elsevier B.V
2019
Abstract
Today, many applications produce and use time series data. The data of this type may contain sensitive information. So they should be protected against unauthorized accesses. In this paper, security issues of time series data are identified and an access and inference control model for satisfying the identified security requirements is proposed. Using this model, administrators can define authorization rules based on various time-based granularities (e.g. day or month) and apply value-based constraints over the accessed times series data. Furthermore, they can define policy rules over the composition of multiple time-series other than the base time-series data. Detecting and resolving...
A new stochastic oil spill risk assessment model for Persian Gulf: Development, application and evaluation
, Article Marine Pollution Bulletin ; Volume 145 , 2019 , Pages 357-369 ; 0025326X (ISSN) ; Raie, M ; Sharif University of Technology
Elsevier Ltd
2019
Abstract
Persian Gulf is a semi-enclosed highly saline reverse estuary that is exposed to the risk of oil spills in offshore oil and gas activities. In the early 2000s, a specific version of NOAA's Trajectory Analysis Planner (TAP II) was developed for Persian Gulf to assist regional organizations in preparing oil spill contingency plans. In this research, a new stochastic model is developed to cover the limitations of TAP II. The new model is based on an advanced trajectory model, which is now linked with high resolution spatiotemporal data of the wind and sea current. In a case study, the developed model is compared with TAP II, and evaluated by multiple tests designed for analysis of uncertainty,...