Trajectory prediction of objects in moving objects databases (MODs) has garnered wide support in a variety of applications and is gradually becoming an active research area. The existing trajectory prediction algorithms focus on discovering frequent moving patterns or simulating the mobility of objects via mathematical models. While these models are useful in certain applications, they fall short in describing the position and behavior of moving objects in a network-constraint environment. Aiming to solve this problem, a hidden Markov model (HMM)-based trajectory prediction algorithm is proposed, called Hidden Markov model-based Trajectory Prediction (HMTP). By analyzing the disadvantages of HMTP, a self-adaptive parameter selection algorithm called HMTP * is proposed, which captures the parameters necessary for real-world scenarios in terms of objects with dynamically changing speed. In addition, a density-based trajectory partition algorithm is introduced, which helps improve the efficiency of prediction. In order to evaluate the effectiveness and efficiency of the proposed algorithms, extensive experiments were conducted, and the experimental results demonstrate that the effect of critical parameters on the prediction accuracy in the proposed paradigm, with regard to HMTP * , can greatly improve the accuracy when compared with HMTP, when subjected to randomly changing speeds. Moreover, it has higher positioning precision than HMTP due to its capability of self-adjustment.
Big data for social transportation brings us unprecedented opportunities for resolving transportation problems for which traditional approaches are not competent and for building the next-generation intelligent transportation systems. Although social data have been applied for transportation analysis, there are still many challenges. First, social data evolve with time and contain abundant information, posing a crucial need for data collection and cleaning. Meanwhile, each type of data has specific advantages and limitations for social transportation, and one data type alone is not capable of describing the overall state of a transportation system. Systematic data fusing approaches or frameworks for combining social signal data with different features, structures, resolutions, and precision are needed. Second, data processing and mining techniques, such as natural language processing and analysis of streaming data, require further revolutions in effective utilization of real-time traffic information. Third, social data are connected to cyber and physical spaces. To address practical problems in social transportation, a suite of schemes are demanded for realizing big data in social transportation systems, such as crowdsourcing, visual analysis, and task-based services. In this paper, we overview data sources, analytical approaches, and application systems for social transportation, and we also suggest a few future research directions for this new social transportation field.
Traffic surveillance has become an important topic in intelligent transportation systems (ITSs), which is aimed at monitoring and managing traffic flow. With the progress in computer vision, video-based surveillance systems have made great advances on traffic surveillance in ITSs. However, the performance of most existing surveillance systems is susceptible to challenging complex traffic scenes (e.g., object occlusion, pose variation, and cluttered background). Moreover, existing related research is mainly on a single video sensor node, which is incapable of addressing the surveillance of traffic road networks. Accordingly, we present a review of the literature on the video-based vehicle surveillance systems in ITSs. We analyze the existing challenges in video-based surveillance systems for the vehicle and present a general architecture for video surveillance systems, i.e., the hierarchical and networked vehicle surveillance, to survey the different existing and potential techniques. Then, different methods are reviewed and discussed with respect to each module. Applications and future developments are discussed to provide future needs of ITS services.
Nowadays, metro systems play an important role in meeting the urban transportation demand in large cities. The understanding of passenger route choice is critical for public transit management. The wide deployment of Automated Fare Collection(AFC) systems opens up a new opportunity. However, only each trip's tap-in and tap-out timestamp and stations can be directly obtained from AFC system records; the train and route chosen by a passenger are unknown, which are necessary to solve our problem. While existing methods work well in some specific situations, they don't work for complicated situations. In this paper, we propose a solution that needs no additional equipment or human involvement than the AFC systems. We develop a probabilistic model that can estimate from empirical analysis how the passenger flows are dispatched to different routes and trains. We validate our approach using a large scale data set collected from the Shenzhen metro system. The measured results provide us with useful inputs when building the passenger path choice model.
Purpose:To use magnetic resonance (MR) imaging and positron emission tomography (PET) dual detection of cardiacgrafted embryonic stem cells (ESCs) to examine (a) survival and proliferation of ESCs in normal and infarcted myocardium, (b) host macrophage versus grafted ESC contribution to serial MR imaging signal over time, and (c) cardiac function associated with the formation of grafts and whether improvement in cardiac function is related to cardiac differentiation of ESCs. Materials and Methods:All animal procedures were approved by the institutional animal care and use committee. Murine ESCs were stably transfected with a mutant version of herpes simplex virus type 1 thymidine kinase, HSV1-sr39tk, and also were labeled with superparamagnetic iron oxide (SPIO) particles. Cells were injected directly in the border zone of the infarcted heart or in corresponding regions of normal hearts in athymic rats. PET and MR imaging were performed longitudinally for 4 weeks in the same animals. Results:ESCs survived and underwent proliferation in the infarcted and normal hearts, as demonstrated by serial increases in 9-(4-[ 18 F]fluoro-3-hydroxymethylbutyl) guanine PET signals. In parallel, the hypointense areas on MR images at the injection sites decreased over time. Double staining for host macrophages and SPIO particles revealed that the majority of SPIO-containing cells were macrophages at week 4 after injection. Left ventricular ejection fraction increased in the ESC-treated rats but decreased in culture media-treated rats, and border-zone function was preserved in ESC-treated animals; however, cardiac differentiation of ESCs was less than 0.5%. Conclusion:Dual-modality imaging permits complementary information in regard to cell survival and proliferation, graft formation, and effects on cardiac function. RSNA, 2009 Supplemental Note: This copy is for your personal, non-commercial use only. To order presentation-ready copies for distribution to your colleagues or clients, use the Radiology Reprints form at the end of this article. Coronary heart disease accounts for 36% of all cardiovascular death and is the leading cause of heart failure in the United States (1). Although postinfarction survival rates have been improved, congestive heart failure caused by a large infarction or progressive unfavorable ventricular remodeling remains a major problem (2). Despite that cardiac transplantation is currently the most effective therapy, the disparity between organ demand and supply limits its applicability. A treatment strategy often referred to as "cellular cardiomyoplasty" is an attempt at cardiac repair through local (intramyocardial, intracoronary) or systemic (intravenous) delivery of a variety of cells, including fetal or neonatal cardiomyocytes, cardiac cells derived from adult atrial appendages, skeletal myoblasts, embryonic stem cells (ESCs), or bone marrow-derived mesenchymal and hematopoietic stem cells. The strategy is based on the potential of these cells to differentiate into cardiomyocytes to repopulate the ...
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